Fuelled by a changing climate, plant pathogens encounter increasingly favourable conditions to spread and wreak havoc on global crop yields. But could artificial intelligence help predict the spread of disease, buying farmers valuable time to take preventative measures?

As part of an effort that took top honours and a $20,000 prize in the recent ProjectX global undergraduate research competition, a team of University of Toronto students proposed the use of a new machine learning architecture to forecast infections of black Sigatoka, a fungal disease that blackens bananas from the inside out.

ProjectX,the brainchild of the U of T Artificial Intelligence student group, challenged teams of undergraduate students from universities around the world to use machine learning to address the impacts of climate change. The competition, which concluded in December, was divided into three categories: infectious disease; weather and natural disaster prediction; and emissions and energy efficiency.

Left to righ (top row):Ziyad Edher, Yuchen Wang, Sornnujah Kathirgamanathan, (bottom row) Matthieu Chan Chee, Minh Duc Hoang andShion Fujimori.

ProjectX organizers maintained a strict firewall between themselves and U of T student competitors to ensure fairness in the competition.

The team from U of T that emerged victorious in the infectious disease category included computer science studentsYuchen Wang,Matthieu Chan Chee,Ziyad Edher,Minh Duc HoangandShion Fujimori; as well asSornnujah Kathirgamanathan, a molecular genetics and microbiology student in the Temerty Faculty of Medicine.

Operating remotely from Toronto, Vancouver, Japan, and Vietnam, the team members focusedon devising a neural network to forecast the infection risk of black Sigatoka.The fungal disease can have devastating consequences for farmers, decreasing yields and driving up costs. The Food and Agriculture Organization of the United Nations reported that, between 2007 and 2009, St. Vincent and the Grenadines faced a 90 per centdecline in banana crop production due to the disease.

For more information: utoronto.ca

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Prize-winning team uses AI to beat banana blight - FreshPlaza.com

Introduction

Lung cancer is one of the leading causes of cancer-related death globally.1 Although there are different types of lung cancer, non-small cell lung cancer (NSCLC) represents 85% of all primary lung tumors. NSCLC is a grim disease that is aggravated by the fact that patients normally either receive their diagnosis at advanced stages or present with recurrent disease after initial locoregional treatment.2 Over the last few decades, conventional chemotherapy, mainly platinum-based chemotherapy, used to be the only therapeutic option for those not eligible for radical intent treatment: a treatment with limited efficacy and very few long-term survivors (5-year overall survival less than 15%). Furthermore, these patients often lacked therapeutic options beyond first-line treatment.3

More recently, though, immune checkpoint molecules involved in tumor immune evasion were identified and immune checkpoint inhibitors (ICIs) were introduced in antitumor immunotherapy. This new therapeutic approach targets an inhibitory receptor, the programmed cell death-1 (PD-1) receptor, to assist the immune system in identifying and neutralizing malignant cells. However, tumor cells may evade the host immunosurveillance by expressing the programmed death-1-ligand 1 (PD-L1) as an adaptive, resistant mechanism to suppress this inhibitory receptor.4 Thus, because PD-L1 up-regulation by tumor cells can protect them from antitumor immune response, the blockade of PD-L1/PD-1 interactions has been recently selected for antitumor immune therapy.5 Agents targeting the PD-1/PD-L1 signaling pathway have shown promising responses in different types of cancer, including NSCLC. These results point to PD-L1 protein expression as a potential predictive marker for a successful blockade of PD-L1/PD-1 interactions.6 However, several challenges remain in producing robust evidence to support the use of this biomarker.

In this context, some studies with NSCLC patients have demonstrated that those with more than 50% PD-L1 positive tumor cells are non-responders to anti-PD-1/PD-L1 treatment. In contrast, others have shown that patients whose tumors do not express PD-L1 are good responders.79 To explain the controversies that affect PD-L1 expression, some studies have considered that the heterogeneity between axis expression and response to PD-1/PD-L1 treatment in NSCLC depends on other factors, such as more precise methods to investigate immune evasion mechanisms and the immune microenvironment, as well as greater knowledge on the immune checkpoint genomic profile and the genetic variants of the PD-L1 gene.1013

Some genetic variants have been shown to affect normal gene activation and transcriptional initiation, and hence influence the amount of mRNA and encoded protein in the cell.14 Non-coding variants also presumably affect genetic regulatory elements, since a majority of driver variants in cancer genomes occur in non-coding regions.15,16

Thus, several studies have investigated the association between PD-1 and PD-L1 genetic variants and the risk of various cancers, but their findings have yet failed to completely elucidate this question.17 A previous study suggested that PD-L1 polymorphism may predict chemotherapy response and survival rates in advanced-stage NSCLC patients after first-line paclitaxel-cisplatin.18 More recently, PD-L1 copy number variations, point mutations, and 3-UTR disruptions have been highlighted as genetic mechanisms of PD-L1 deregulation.19 Furthermore, previous research on Brazilian patients suggested that their ethnic background could account for their distinct cancers molecular profile, perhaps due to their characteristic genetic admixture, inherited from European, African, and Native American ancestors.2022

We hypothesize that PD-L1 non-coding genetic variants modulate the function of this immune checkpoint in NSCLC. To explore this issue, we investigated fifteen PD-L1 non-coding genetic variants using next-generation sequencing (NGS) in a Brazilian cohort, aiming to uncover the effect of their ethnic admixture on NSCLC. We also combined our analyses with an in-silico approach to predict the impact of these genetic variants on the disease. We evaluated the associations between PD-L1 protein expression level and clinicopathological characteristics, including the prognosis of NSCLC patients undergoing surgical resection, glimpsing the impact of genetic variants on post progression survival (PPS) and overall survival (OS). Herein, in this context, we intend to expand the existing literature on PD-L1 gene alterations at the genetic level and their impact on NSCLC in patients from different ethnicities, thus increasing the knowledge about the molecular basis of immunotherapy biomarkers.

In this retrospective multi-center study, we obtained archival formalin-fixed paraffin-embedded histologic tumor sections from 70 patients diagnosed with NSCLC (33 adenocarcinomas [ADC], 24 squamous cell carcinoma [SqCC] and 13 large cell carcinoma [LCC]) who underwent surgical resection between January 1, 1995, and December 31, 2015. Patients had been treated at the Hospital das Clnicas of the University of So Paulo Medical School (HC-FMUSP), at the Heart Institute of the University of So Paulo (INCOR), at the Cancer Institute of So Paulo (ICESP), and at the A.C. Camargo Cancer Center in So Paulo, Brazil.

All samples were histologically reviewed by lung pathologists who selected samples with at least 30% of lung cancer cells before nucleic acid extraction. The samples were classified using the 2017 International Association for the Study of Lung Cancer (IASLC) classification system.23 The clinicopathological features of patients were obtained from the medical records. The study was approved in accordance with the ethical standards of the responsible committee on human experimentation local (Research Ethics Committee of University of So Paulo Medical School - CAAE: 79769017.1.0000.5440; opinion number: 2.673.320) and with the 1964 Helsinki declaration. A waiver of the requirement for informed consent was obtained from committee, and to identity of the subjects under this retrospective analysis was omitted and anonymized.

We performed a Multiplex immunofluorescence (mIF) staining using methods that had been previously described and validated.24,25 Four-micrometer-thick consecutive TMA sections were stained using an automated staining system (BOND-RX; Leica Biosystems, Buffalo Grove, IL) to characterize PD-L1 (clone E1L3N, dilution 1:100; Cell Signaling Technology, Danvers, MA). The PD-L1 marker was stained with its respective fluorophore from the Opal 7 kit (catalogue #NEL797001KT; Akoya Biosciences/PerkinElmer, Waltham, MA). A complete validation using immunofluorescence (IF) allowed us to obtain a uniform, specific, and appropriate signal across all the channel; ie, a well-balanced staining pattern for the multiplex staining.24,25 We also defined and optimized the correct fluorophore signals between 10 and 30 counts of intensity to maintain good balance and similar thresholds of intensity across all antibodies. In parallel, to detect possible variations in staining and optimize the separation of the signal, positive and negative (autofluorescence) controls were included during the staining process to ensure that all the antibodies performed well together. Autofluorescence controls with an expected spectral resolution of 488nm were able to accurately remove the autofluorescence from all the label signals during the analysis. The stained slides were then scanned using a multispectral microscope, the Vectra Polaris 3.0 imaging system (Akoya Biosciences/PerkinElmer, Waltham, MA), under fluorescence conditions.

Multispectral images of tumor sections from each core were analyzed with inForm 2.2.1 (Akoya Biosciences/PerkinElmer, Waltham, MA) software Individual cells, which were defined by nuclei staining and identified by the InForm cell segmentation tool, were subjected to a phenotyping pattern-recognition learning algorithm to characterize co-localization of the various cell populations using panel labeling.26 The panel labeling was as follows: Malignant cells (MCs), with the AE1/AE3+ marker, including those with and without PD-L1 expression (AE1/AE3+ PD-L1+ and AE1/AE3+ PD-L1-, respectively). The individual cell phenotype report produced by the InForm software was processed using Excel 2010 (Microsoft. Houston, TX), and a final summary of the data, which contained the median of each individual phenotype (given as number of cells/mm2) and the percentage of macrophages and MCs expressing PD-L1, was created for statistical analysis. If the percentage of MCs or macrophages expressing PD-L1was greater than the median value, the PD-L1 expression was considered positive. If the percentage of macrophages or MCs expressing PD-L1 was lower than or equal to the median, the PD-L1 expression was considered negative.

Genomic DNA (gDNA) was extracted from frozen NSCLC tissue using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) according to the manufacturers recommendations. DNA concentration was measured using the Qubit 3.0 Fluorometer (Invitrogen, Life Technologies, CA, USA). DNA integrity was assessed using the Bioanalyzer 2100 system (Agilent Technologies, CA, USA).

We performed a PD-L1 (CD274) full gene screening by deep targeted sequencing using the TruSeq Custom Amplicon Panel v1.5 kit (TSCAP, Illumina, SanDiego, CA) and the MiSeq platform (Illumina, SanDiego, CA). The DNA libraries were performed according to the manufacturers instructions and consisted of 150 bp paired-end reads (300 cycles).

We performed an NGS data analysis on the Molecular Genetics and Bioinformatics Laboratory of the Experimental Research Unit (UNIPEX) at the Medical School of So Paulo State University (FMB-UNESP). Sequencing quality was assessed by FastQC. Reads were aligned to the human genome (hg19, GRCh37) with BWA software, and SAM tools converted the alignment results to BAM format.27 Next, the mapped reads underwent variant calling for SNP with GATK command line tools, including HaplotypeCaller, SelectVariants, and VariantFiltration programs with default parameters. After the calling step, the variants were annotated using the VEP28 software. Coverage depth was a priori set at 100. Variants had to have >10 reads of position depth (PD) and/or >6 reads of allele depth (AD) and/or an AD/PD ratio of >0.05 and/or a population frequency higher than 1% (popfreq_all >0.01) were included in the study. Finally, variants were compared using ABraOM, a web-based public database of Brazilian genomic variants.29

Several tools were used to predict potential functional effects of SNPs on non-coding binding sites, such as splice sites and binding sites for transcription factors, exonic splicing enhancers (ESEs), and microRNA (miRNA). The impact of each genetic variant was assessed using VarSome30 an integrated search engine that allows access to several databases, forecasting tools, and publications on a single website. Variant pathogenicity was reported using an automatic variant classifier that evaluates each submitted variant according to guideline of the American College of Medical Genetics and Genomics (ACMG) and classifies it as either pathogenic, likely pathogenic, likely benign, benign or uncertain significance. Varsome predicts the pathogenicity of each variant through a DANN31 score, a methodology for scoring deleterious annotations of genetic variants using neural networks that results in a number ranging from 0 to 1. Higher DANN scores represent greater variant deleteriousness.31

Next, we applied the Genomic Evolutionary Rate Profiling (GERP)32,33 conservation score. This score is used to calculate the reduction of substitutions in a multi-species sequence alignment when compared to a neutral expectation. GERP scores >5.5 are strongly associated with a purifying selection. Mutations that occur at highly conserved sites in many species are assumed as harmful and therefore contribute to the genetic load within a species.

Finally, we used two tools, SNPinfo (FuncPred)34 and RegulomeDB,35 to track SNPs according to their functions. SNPinfo is a web server that helps researchers investigate SNPs in studies of genetic association and provide different pipelines for SNP selection, whereas RegulomeDB is an online composite database and prediction tool to annotate and prioritize potential regulatory variants from the human genome.35 RegulomeDB divides the variants into six categories: category 1 variants are likely to affect binding and are linked to the expression of a gene target, category 2 variants are likely to affect binding, category 3 variants are less likely to affect binding, and category 4, 5, and 6 variants have minimal binding evidence.35

The allelic and genotypic frequencies of the PD-L1 polymorphisms found in NSCLC were calculated by Hardy Weinberg equilibrium ([1 _ (hC 2H)]/2N, where h stands for a heterozygous genotype, H for homozygous genotype and N for the number of samples). Associations between polymorphisms, PD-L1 protein expression, and the clinicopathological parameters of NSCLC patients were investigated by Chi-square test. The prognostic value of each polymorphism was assessed by a survival analysis using the KaplanMeier method with the Log rank test for statistical significance. In addition, Coxs proportional hazards regression models were used in a multivariate analysis to test the association between SNPs and PPS and OS. PPS was considered as the period from tumor progression until death or last follow-up. OS was defined as the time from curative surgery to death or last date known to be alive. The statistical software program IBM SPSS (version 22; Armonk, NY, USA) performed all analyses. Differences were considered statistically significant at P<0.05.

Of the 70 patients included in the study, 33 presented with ADC (47.1%), 24 with SqCC (34.3%), and 13 with LCC (18.6%). The clinical characteristics by histologic types are summarized in Table 1. While SqCC cases were more frequent in males (81.8%), ADC cases were equally distributed between genders, and LCC cases were close to equal distribution (male 55.6%, female 44.4%). All histological types were more frequent in patients aged 63 years or younger. 8 patients reported a history of tobacco smoking in the ADC group (72.7%) and in the SqCC group (88.9%), versus 3 patients in the LCC group (50.0%). All the histological subtypes included advanced stages of disease (9 cases in ADC, 6 cases in SqCC, and 4 cases in LCC). Most of the patients had not received either chemotherapy (12 cases to ADC, 8 cases to SqCC, and 6 cases to LCC) or radiation therapy (18 cases to ADC, 10 cases to SqCC, and LCC) as adjuvant treatment. Malignant cells expressed PD-L1 above the median in 7 LCC cases (70.0%), the most relevant expression compared to the other two histological subtypes. The median follow-up was 66 (12144) months. None of the analysis revealed significant differences between histological types (P>0.05).

Table 1 Demographic and Clinicopathological Characteristics of 70 NSCLC Patients

All NSCLC patients who underwent surgical resection were successfully genotyped for fifteen PD-L1 SNPs: rs76805387T>C, rs4742098A>G, rs47946526A>G, rs10217310G>T, rs7864231G>A, rs41280725C>T, rs573692330A>G, rs1011769981G>A, rs41280723T>C, rs138135676T>C, rs4143815G>C, rs2297136G>A, rs148242519G>A, rs41303227C>T, and rs7041009G>A. Supplementary Table 1 shows the SNP identification numbers, allele and genotype frequencies, and P-value for HWE. Of the 15 SNPs studied, 11 were found to be monomorphic, whereas 4 SNPs, namely rs4742098, rs4143815, rs2297136, and rs7041009, were polymorphic in NSCLC. Monomorphic SNPs were excluded from further analysis. All the polymorphic SNPs were found to be in equilibrium (P>0.05) for HWE. The allele frequency of our cohort was compared to different populations in the 1000 Genomes Project (Supplementary Table 2).

We performed stratified analyses on the associations between clinical characteristics and the four PD-L1 polymorphisms with different genotypic distributions. Table 2 shows each SNP genotype frequency and their associated clinicopathological characteristics. Three of the four PD-L1 gene polymorphisms (rs4742098, rs4143815, and rs7041009) were significantly associated with relapse (P=0.01; P=0.05; P=0.02, respectively). For the rs4742098 variant, carriers of the G allele (AG or GG genotypes) were less likely to relapse (P=0.01). Similarly, for rs4143815, carriers of the alternative C allele (CG or CC genotypes) were also less likely to relapse (P=0.05). In rs7041009, however, carriers of the alternative allele A (AG or GG genotypes) were more likely to relapse (P=0.02). Moreover, GG genotype (reference) of rs7041009 showed a significant correlation with age, being more prevalent among younger patients (16 patients, or 69.6%), and status, being more prevalent among patients who were alive (11 patients, or 84.6%), compared to carriers of the A allele (P=0.02 and P<0.01, respectively). No statistical significance was observed in the association between rs2297136 genotypes and clinicopathological variants.

Table 2 Clinicopathological Characteristics of 70 NSCLC Patients Stratified by the PD-L1 Polymorphisms rs4742098, rs4143815, rs2297136 and rs7041009

The correlation between PD-L1 protein expression and PD-L1 gene polymorphisms are shown in Table 2. There were no statistically significant associations between PD-L1 protein expression in malignant cells and PD-L1 gene polymorphisms. In our cohort, the four PD-L1 gene polymorphisms were in non-coding regions and, apparently, cause no interference in PD-L1 protein expression in NSCLC malignant cells. However, when we correlated PD-L1 protein expression with histological subtype, we observed that the expression in malignant cells was above the median in 70% of patients with LLC, in contrast with 45.8% and 47.4% of patients with ADC and SqCC, respectively.

Our first statistical test examined the individual effect of patients characteristics to estimate statistical differences in survival using the KaplanMeier method (Table 3). Patients younger than 63 years showed increased OS, 111.62 vs 66.54 months in older patients (P=0.05). Choice of treatment was also an independent factor in diagnosis, with patients who did not receive radiotherapy presenting a better survival rate when compared with those who were treated with radiotherapy, 94.43 vs 12.00 months, respectively (P<0.01). Patients who presented disease recurrence had lower survival rates and poorer prognostic when compared with those who did not relapse, 48.23 vs 123.10 months, respectively (P<0.01).

Table 3 A Survival Analysis Conducted by the KaplanMeier Method Showing the Difference in the Means of the Log Rank Test According to the Optimal Upper and Lower Binary Cut-off Limits of Different Variables

Moreover, differences in the genotypes of PD-L1 polymorphisms seemed to also impact the prognosis of NSCLC patients. PD-L1 rs7041009, for instance, led to a statistically significant difference in OS (Figure 1), with carriers of the A allele of rs7041009 having lower OS than carriers of the GG genotype (reference), 59.00 vs 116.93 months, respectively (P<0.01).

Figure 1 KaplanMeier survival curve for PD-L1 rs7041009 G>A. A allele carriers (AG+AA) presented worse prognosis and a lower survival rate when compared to GG genotyped patients (P<0.01).

Next, using a univariate Cox Regression analysis, we were able to associate the following variables with a lower risk of death: the absence of radiotherapy treatment, relapse, and GG genotype of PDL1 rs7041009 (Table 4). However, after feeding these variables into a multivariate analysis, only the absence of radiotherapy treatment and relapse were considered to be independent factors for OS (HR 9.82, P=0.02; HR 6.15, P=0.04, respectively).

Table 4 Variables Associated with Overall Survival (OS) in 70 Patients Diagnosed with NSCLC. Univariate and Multivariate Analyses Employing a Cox Proportional Hazards Model

Then, we introduced the PD-L1 polymorphisms into the Cox model, controlling for radiotherapy treatment and tumor relapse. Of the four SNPs, only rs7041009 was identified as a co-dependent factor associated with radiotherapy and relapse. We thus inferred that patients with NSCLC who carried the A allele (AG/AA) presented a higher risk of relapse in the presence of radiotherapy, resulting in a poorer prognosis and decreased survival rates than patients who carried the rs7041009 GG genotype. In relapsed patients, we observed that the PD-L1 polymorphisms rs7041009 and rs4742098 might have an impact on PPS (Figure 2). Patients with the rs7041009 GG genotype had a higher PPS than those with the alternative A allele of rs7041009 (AG/AA), 110.98 vs 56.18 months, respectively (P<0.01); whereas, patients who carried the reference rs4742098 AA genotype had lower PPS than those who carried the alternative G allele of rs4742098 (AG/GG), 56.00 vs 115.71 months, respectively (P=0.02).

Figure 2 KaplanMeier survival curves estimating post-progression survival (PPS) in NSCLC patients according to PD-L1 polymorphisms. (A) KaplanMeier survival curve for rs7041009 G>A. A allele carriers (AG+AA) presented worse prognosis and a lower PPS rate when compared GG genotyped patients (P<0.01); (B) KaplanMeier survival curve for rs4742098 A>G. G allele carriers (AG+GG) had a higher PPS rate and better prognosis when compared AA genotyped patients (P=0.02).

The in silico analysis predicted the PD-L1 variants rs4742098 (c.*2635A>G), rs4143815 (c.*395G>C), rs2297136 (c.*93G>A), and rs7041009 (c.682+122G>A) to be benign (Table 5). Not only was the DANN score low for all four variants (0.8226, 0.6475, 0.7056, and 0.5428, respectively), but their GERP score was also lower than 5.5 (1.74, 2.38, 4.4, and 1.81, respectively), indicating that these variants are found in non-conserved positions and are unlikely to be harmful.

Table 5 List of the Selected Non-Coding SNP and the Tools Used to Study Them

SNPinfo predicted miRNA-binding function to be affected by two of these variants, namely rs2297136 and rs4143815. Rs2297136 was predicted to affect the binding function of hsa-miR-324-5p and hsa-miR-632, whereas rs4143815 was found to correlate with hsa-miR-1252, hsa-miR-1253, hsa-miR-539, hsa-miR-548, and hsa-miR-570 (Table 6). RegulomeDB was then used to complement the SNP analysis. Three of the four SNPs, rs4742098, rs4143815, and rs2297136, had a RegulomeDB score of 5, whereas rs7041009 had a score of 6, meaning that all four variants show minimal binding evidence (Table 5).

Table 6 List of the 3 UTR SNPs Analyzed in FuncPred and Their miRNA Motif

Lung cancer has a high mortality rate and lacks suitable markers for early diagnosis and prognosis. Thus, it is essential to detect the best potential biomarker out of the several genetic and protein markers. Fortunately for patients, the translational impact of such findings is rapidly increasing, and the stimulation of immune response by ICIs has emerged as a dramatic paradigm shift in the treatment of advanced tumors, mainly NSCLC.19,36 PD1/PDL1 monoclonal antibodies have shown potential efficacy in advanced squamous-cell and non-squamous NSCLC.37,38 However, despite the remarkable success achieved by immunotherapy so far, its effectiveness still seems to vary among cancer patients.19 The expression of PD-L1 on tumor cells remains the only recognized predictive factor for immunotherapy response in NSCLC patients; however, patients without PD-L1 expression on tumor cells may also respond to immunotherapy.3943 Based on these findings, the present study inferred that PD-L1 non-coding genetic variants could help predict the prognosis of patients with NSCLC and impact disease recurrence and OS.

In our cohort of 70 NSCLC specimens, we evaluated PD-L1 protein expression in malignant cells by PD-L1 multiplex immunofluorescence (mIF) assays, using the Cell Signaling E1L3N clone and image analysis, and investigated PD-L1 polymorphisms by NGS sequencing. This method resulted in the detection of high PD-L1 expression in LCC malignant cells when compared to other histological subtypes, suggesting that LCC patients may benefit from ICIs. As described by Shimoji et al,44 PD-L1 expression using the Cell Signaling E1L3N clone was significantly correlated with a consistent vimentin expression, increased Ki-67 labeling index and poor prognosis in ADC but not in SqCC. Other studies have reported that PD-L1 was detected at significantly higher frequencies in SqCC than in ADC of the lung.44,45 Cha et al46 found that PD-L1 expression using the SP142 clone was significantly associated with an ADC solid subtype histology, p53 aberrant expression, and poor prognosis.

We also assessed PD-L1 polymorphisms. Of the fifteen genetic variants genotyped, eleven were monomorphic. The four potential variants (rs4742098, rs4143815, rs2297136, and rs7041009) present in the non-coding region were correlated with the clinicopathological characteristics of the NSCLC patients and were submitted to an in silico analysis investigating their functional role. The MAF of the rs4742098, rs4143815, and rs7041009 polymorphisms was consistent with the genotype frequency among European and Mixed Americans populations present in The 1000 Genomes Project, whereas the G allele in the rs2297136 polymorphism was the main allele in our cohort to show racial differences.

When assessing patient prognosis, three of the four PD-L1 variants rs4742098, rs4143815, and rs7041009 were significantly associated with disease recurrence. Carriers of the G allele (individuals with the AG or GG genotypes) of rs4742098 were less likely to relapse compared to carriers of the homozygous AA genotype. Similar findings were published by Du and colleagues,47 who reported that the AG genotype differed from the AA genotype in terms of risk of NSCLC recurrence. In the case of rs4143815G, patients with the alternative C allele were less likely to relapse in our study, in agreement with Nomizo et als report.48 In their study, the authors even suggested that this polymorphism might be a biomarker for nivolumab efficacy.48 Finally, in our study, for rs7041009G>A, carriers of the alternative G allele were more likely to exhibit relapse. The rs7041009 GG genotype also showed a significant correlation with age, being more present in younger patients, and with status, being more present in patients who are alive, compared to carriers of the A allele. Rs7041009 (c.682+122G>A) is located at position 2377 in intron 4 of the PD-L1 gene. However, little is known about the exact function of this genetic variation, except that it is located near the transcription factor binding site.

Our cohort showed a significant association between these PD-L1 polymorphisms and OS in NSCLC. 18 Patients presenting the GG genotype of rs7041009 benefited from longer OS. In addition, our findings indicated that both the rs7041009G and rs4742098G polymorphisms were significantly related to a longer PPS. The clinical impacts of PD-L1 variants had also been investigated by previous studies. Zhao et al49 suggested that patients with the GG genotype of another PD-L1 polymorphism (rs822336) had worse disease-free survival and OS in a Chinese patient population.

Further contribution was provided in that respect by Lee et al50 who demonstrated that rs4143815 and rs2297136 were significantly associated with clinical outcomes after chemotherapy. Of 379 patients with NSCLC treated with first-line paclitaxelcisplatin chemotherapy, those carrying the rs4143815 G allele responded better to chemotherapy and had gains in overall survival. In our study, however, the polymorphism rs2297136 showed no significant association with clinical outcome, a finding that was corroborated by Zhao et al.49 This difference might be explained by the heterogeneity of patients enrolled in each study, and further research is needed to settle this question.

In our study, we were unable to find any statistical significance between the rs4742098, rs4143815, rs2297136, and rs7041009 genotypes and PD-L1 protein expression in malignant cells. However, recent data have helped to shed light on the impact of PD-L1 genetics on PD-L1 expression, though the existing results remain controversial. Recently, Tao and colleagues51 showed that rs4143815 and rs10815225 in the PD-L1 gene contributed to PD-L1 overexpression in gastric cancer. So far, Lee et al18 have conducted the largest study on PD-L1 polymorphisms and PD-L1 expression in NSCLC. The authors showed that rs822336C, rs822337A and rs4143815G were associated with worse OS in NSCLC patients but found no significant correlation between PD-L1 expression and the genotypes of these polymorphisms. Krawczyk et al52 demonstrated that carriers of the rs822335 CC genotype were predisposed to higher expression of the PD-L1 protein in NSCLC tumor cells, whereas rs822336 had no effect on PD-L1 expression in these cells. Their results are consistent with our findings, but future research is needed to clarify remaining confounders.

In our study, using in silico approaches, we report that rs4742098, rs4143815, rs2297136, and rs7041009 can be considered benign variants. However, little is known about the effect that mutations in conserved non-coding regions might have on fitness and how many of them are present in the human genome as deleterious polymorphisms. Moreover, rs2297136 was predicted to affect the miRNA-binding function of hsa-miR-324-5p and hsa-miR-632, whereas the variant rs4143815 was found to correlate with hsa-miR-1252, hsa-miR-1253, hsa-miR-539, hsa-miR-548, and hsa-miR-570. In this context, others have reported that variants in the 3UTR region of the PD-L1 gene can affect the interaction of miRNAs, possibly resulting in PD-L1 underexpression.53 Therefore, additional studies are necessary to validate our findings. However, there are limitations to our analysis. We did not perform a casecontrol approach and our cohort comprises a relatively small sample size. Nonetheless, to our knowledge, our research on the effect of the rs7041009 polymorphism of PD-L1 gene on NSCLC patients is unique.

We believe this study is also the first to evaluate variants in the non-coding region of the PD-L1 in Brazilian patients with NSCLC, since most studies of PD-L1 polymorphisms have been conducted in Asian patients. Thus, we consider this exploratory study as a pioneer in the understanding of PD-L1 polymorphisms in a genetic admixed population.

We appreciate all subjects who participated in this study and the Illumina members for assistance with the initial runs.

This study was supported by the So Paulo Research Foundation, FAPESP (grant numbers 2013/14277-4 and 2018/20403-6).

The authors report no conflicts of interest related to this work.

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[Full text] Relevance of PD-L1 Non-Coding Polymorphisms on the Prognosis of a Gene | PGPM - Dove Medical Press

TBINGEN, Germany--(BUSINESS WIRE)--February 19, 2021 -- Illumina, Inc. (Nasdaq: ILMN) today announced an agreement with the Institute of Medical Genetics and Applied Genomics at the University Hospital of Tbingen to assess the value of whole-genome sequencing (WGS) as a first-line diagnostic test for patients with genetic diseases and familial cancer syndromes. Illumina will support the new investigator-initiated study, called the Ge-Med Project, with sequencing, analysis and health economic expertise.

The Institute is the first laboratory in Germany accredited to perform clinical WGS. Previously, it used whole exome sequencing for the diagnosis of rare disease conditions which involves sequencing only around 1% of the genome known to contain the coding regions that provide instructions for making proteins.

The move to WGS is based on a two-year feasibility study by the Institute, supported by Illumina, which found that WGS provided improved diagnosis across a range of rare diseases. For example, as many as 75% of genetic eye diseases were accurately diagnosed using WGS, including some forms of disease that could only be identified by sequencing the entire genome. Similar results were found for rare childhood cancers and for conditions that cause developmental delay in children.

In addition to expanding the range of conditions for diagnosis, the new study will examine the ability of WGS to generate scores for the risk of common diseases based on genomic data. Known as a polygenic risk score, this will help identify individuals that may benefit from personalized healthcare management.

We are delighted to be able to study whole genome sequencing as a diagnostic in an expanded range of conditions because we have demonstrated that it changes the management of patients who previously remained unresolved after whole exome and other sequencing approaches, said Tobias Haack, Head of Molecular Diagnostics at the Institute of Medical Genetics and Applied Genomics, University Hospital of Tbingen.

We are proud to support the University Hospital of Tbingen on this important step in their genomic work, said Dr. Phil Febbo, Chief Medical Officer, Illumina. Offering a clear diagnosis as well as disease risk for common conditions will give patients peace of mind and offer actionable steps to improve their overall health.

Professor Olaf Rie said, We know that the exome isnt the whole story when looking for answers to rare diseases and we have proven the value that WGS brings to families who otherwise would wait years for a diagnosis, or may never even receive one. Through the new study, we hope to help Germany lead the way in applying cutting edge genomics to improve healthcare.

About Illumina

Illumina is improving human health by unlocking the power of the genome. Our focus on innovation has established us as the global leader in DNA sequencing and array-based technologies, serving customers in the research, clinical, and applied markets. Our products are used for applications in the life sciences, oncology, reproductive health, agriculture, and other emerging segments. To learn more, visit http://www.illumina.com and connect with us on Twitter, Facebook, LinkedIn, Instagram, and YouTube.

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Illumina and the University Hospital of Tbingen Evaluate Potential of Whole Genome Sequencing to Improve Diagnosis of Full Range of Genetic Diseases -...

SALT LAKE CITY, Feb. 12, 2021 (GLOBE NEWSWIRE) -- Myriad Genetics, Inc.. (NASDAQ: MYGN), a leader in genetic testing and precision medicine, announced today additional data further validating the prognostic power of its Prolaris test and its ability to help accurately predict which men with more aggressive prostate cancer will benefit from intensification of therapy and which patients may safely avoid such treatments. This second validation study was presented during an oral presentation at the American Society of Clinical Oncology Genitourinary Cancer Symposium (ASCO-GU) by Jonathan Tward M.D., Ph.D, associate professor in the Department of Radiation Oncology at the University of Utah.

According to estimates by the American Cancer Society, 248,530 new cases of prostate cancer are expected to be diagnosed this year in the U.S. While early screening tests have helped reduce the mortality rate, they can often result in overdiagnosis and overtreatment of a disease that is clinically insignificant. The Prolaris test can more accurately predict the aggressiveness of the cancer allowing for more precise treatment and avoidance of more intense therapies with a patients parallel morbidities.

There are many viable treatment paths for men with prostate cancer, said Dr. Tward. This new data helps distinguish the most appropriate personalized treatment path for each patient based on how their specific tumor is behaving. For some men, this means being able to avoid overtreating patients with therapies including hormone treatment that can momentously impact their quality of life, while still appropriately treating their prostate cancer.

The new data comes from a second study following previous data, recently published in Clinical Genitourinary Cancer in January 2021, that incorporated men treated surgically or with radiation therapy. This new study combined a Prolaris molecular risk score threshold with a clinical model for predicting a patients benefit from androgen deprivation therapy. Prolaris determined that about one of every two men with unfavorable intermediate-risk and one of every five men with high-risk prostate cancer are below the proposed threshold associated with aggressive disease and can therefore safely be treated with less intense therapy while maintaining the benefits of treatment. Additional key findings revealed that the Prolaris test was an accurate predictor of progression to metastatic disease.

Myriad Genetics was the first company to offer a test that directly measures the molecular biology of an individual patients prostate cancer, said Todd D. Cohen, M.D., vice president of Medical Affairs for Urology at Myriad Genetics. This study by Dr. Tward and his team is another strong validation of the prognostic power of the Prolaris test and our ongoing commitment to providing healthcare professionals with the tools needed to determine the most effective treatments and monitoring strategies for each patient.

In March 2020, the National Comprehensive Cancer Network updated its professional guidelines to include biomarker testing for unfavorable intermediate and high-risk patients with prostate cancer. With the updated guidelines, Prolaris was one of only two prognostic tests to be considered for those expanded indications. Approximately 60% of men with prostate cancer currently have insurance or Medicare access to Prolaris, and Myriad continues to work toward expanding access so that every man who is facing difficult treatment decisions will be able to utilize the full benefits of the test.

About ProlarisProlaris is a genetic test developed by Myriad Genetics that directly measures tumor cell growth. The Prolaris test paired with other clinical and pathologic variables provides the level of aggressiveness of a patients individual prostate cancer and assesses risk of death or the development of metastatic disease from prostate cancer. For more information visit: http://www.prolaris.com.

About Myriad GeneticsMyriad Genetics Inc., is a leading genetic testing and precision medicine company dedicated to transforming patient lives worldwide. Myriad discovers and commercializes genetic tests that determine the risk of developing disease, accurately diagnose disease, assess the risk of disease progression, and guide treatment decisions across medical specialties where critical genetic insights can significantly improve patient care and lower healthcare costs. For more information, visit the Company's website:www.myriad.com.

Myriad, the Myriad logo, BART, BRACAnalysis, Colaris, Colaris AP, myPath, myRisk, Myriad myRisk, myRisk Hereditary Cancer, myChoice, myPlan, BRACAnalysis CDx, Tumor BRACAnalysis CDx, myChoice CDx, Vectra, Prequel, Foresight, GeneSight, riskScore and Prolaris are trademarks or registered trademarks of Myriad Genetics, Inc. or its wholly owned subsidiaries in the United States and foreign countries. MYGN-F, MYGN-G.

Safe Harbor StatementThis press release contains "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995, including statements related to the validation study presented during at ASCO-GU by Jonathan Tward M.D., Ph.D; expanding access so that every man who is facing difficult treatment decisions will be able to utilize the full benefits of the Prolaris test; and the Companys strategic directives under the caption "About Myriad Genetics." These "forward-looking statements" are based on management's current expectations of future events and are subject to a number of risks and uncertainties that could cause actual results to differ materially and adversely from those set forth in or implied by forward-looking statements. These risks and uncertainties include, but are not limited to: uncertainties associated with COVID-19, including its possible effects on our operations and the demand for our products and services; our ability to efficiently and flexibly manage our business amid uncertainties related to COVID-19; the risk that sales and profit margins of our molecular diagnostic tests and pharmaceutical and clinical services may decline; risks related to our ability to transition from our existing product portfolio to our new tests, including unexpected costs and delays; risks related to decisions or changes in governmental or private insurers reimbursement levels for our tests or our ability to obtain reimbursement for our new tests at comparable levels to our existing tests; risks related to increased competition and the development of new competing tests and services; the risk that we may be unable to develop or achieve commercial success for additional molecular diagnostic tests and pharmaceutical and clinical services in a timely manner, or at all; the risk that we may not successfully develop new markets for our molecular diagnostic tests and pharmaceutical and clinical services, including our ability to successfully generate revenue outside the United States; the risk that licenses to the technology underlying our molecular diagnostic tests and pharmaceutical and clinical services and any future tests and services are terminated or cannot be maintained on satisfactory terms; risks related to delays or other problems with operating our laboratory testing facilities and our healthcare clinic; risks related to public concern over genetic testing in general or our tests in particular; risks related to regulatory requirements or enforcement in the United States and foreign countries and changes in the structure of the healthcare system or healthcare payment systems; risks related to our ability to obtain new corporate collaborations or licenses and acquire new technologies or businesses on satisfactory terms, if at all; risks related to our ability to successfully integrate and derive benefits from any technologies or businesses that we license or acquire; risks related to our projections about our business, results of operations and financial condition; risks related to the potential market opportunity for our products and services; the risk that we or our licensors may be unable to protect or that third parties will infringe the proprietary technologies underlying our tests; the risk of patent-infringement claims or challenges to the validity of our patents or other intellectual property; risks related to changes in intellectual property laws covering our molecular diagnostic tests and pharmaceutical and clinical services and patents or enforcement in the United States and foreign countries, such as the Supreme Court decisions in Mayo Collab. Servs. v. Prometheus Labs., Inc., 566 U.S. 66 (2012), Assn for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576 (2013), and Alice Corp. v. CLS Bank Intl, 573 U.S. 208 (2014); risks of new, changing and competitive technologies and regulations in the United States and internationally; the risk that we may be unable to comply with financial operating covenants under our credit or lending agreements; the risk that we will be unable to pay, when due, amounts due under our credit or lending agreements; and other factors discussed under the heading "Risk Factors" contained in Item 1A of our most recent Annual Report on Form 10-K for the fiscal year ended June 30, 2020, which has been filed with the Securities and Exchange Commission, as well as any updates to those risk factors filed from time to time in our Quarterly Reports on Form 10-Q or Current Reports on Form 8-K. All information in this press release is as of the date of the release, and Myriad undertakes no duty to update this information unless required by law.

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New Study from Leading University of Utah Radiation Oncologist Validates Ability of Myriad Genetics' Prolaris test to Guide Treatment for Prostate...

Linda Chalker-Scott

By Brian C. Clark

From sourdough to home-improvement projects, the coronavirus pandemic has inspired a renaissance in quotidian creativity.

Gardening, too, has blossomed in popularity in the past year and thats a good thing, said Linda Chalker-Scott, an urban horticulturist and professor in the Washington State University Department of Horticulture. Gardening, she said, is great for your mental, physical, and spiritual wellbeing.

Chalker-Scotts latest book is a perfect fit for the times.

Gardening with Native Plants of the Pacific Northwest was recently published in a much revised and updated third edition to great acclaim. The lavishly illustrated book won the 2020 Award of Excellence in Gardening and Gardens from the Council on Botanical and Horticultural Libraries, while Chalker-Scott garnered the R.W. Harris Authors Citation Award from the International Society of Arboriculture.

Gardening with Native Plants was originally published in 1986 by the University of Washington Press and authored by longtime UW botanist Arthur Kruckeberg, with a second revised edition in 2006. The third edition, Chalker-Scott said, was a monumental, eight-year project.

An internationally recognized expert on the science of gardening, Chalker-Scott is also a prolific writer. Shes a founding member of the highly regarded Garden Professors blogging team, which answers gardeners questions (and busts gardening myths) with science, and the author of numerous Extension publications covering a wide variety of gardening and plant-health related topics.

Chalker-Scott was tapped by the UW Press editorial team to revise the book for a new edition. Given her expertise, she was the natural choice. I was very flattered. I brought the practical science behind gardening to the new edition, she said, and relied on a team of experts to make the book something totally new.

Chalker-Scott said she knew Art Kruckeberg socially when she was a faculty member at UW in the late 90s and early 00s. He was already retired, she said. The first and second editions of Gardening with Native Plants were always best sellers, but by the time for a third edition, he was in his 90s.

When it was published 35 years ago, Kruckebergs original edition had descriptions and black and white illustrations of some 250 plants. The third edition describes a whopping 900 plants, all with color photos that had to be sourced. To further complicate matters, molecular genetics in the past couple of decades has overturned our understanding of the relatedness of plantschanging the names of entire families of plants, much to the frustration of gardeners and scientists alike, Chalker-Scott writes in the preface.

Richard Olmstead, a UW biologist, wrote the foreword for the new edition and guided the taxonomic revisions, providing both new and old scientific names.

Nearly a thousand color photos were donated for use in the book, a monumental task curated by Sami Gray. Chalker-Scott said she met Gray through the Garden Professors Facebook group, a stroke of serendipitous luck that also resulted in Gray writing descriptions of the new plants. Samis a great writer in her own regard, Chalker-Scott said, who was able to channel Arts voice so closely that you will be hard-pressed to identify which entries are hers and which are Arts. I cant believe how lucky I was to find her.

One thing that has been omitted from the new edition is the location of native plant populations. Harm has been done all over the world by native-plant collectors, Chalker-Scott said. Art would describe locations and how to collect seeds without digging them up, but, she adds, while most collectors are ethical, it only takes a tiny minority to decimate and damage a microenvironment due to encroachment. Besides, native plant nurseries are by definition local, so support them. Theres lots of information on how to propagate native plants in home gardens.

Chalker-Scott said she has always been a gardener but never got into the science of it until she realized how very little scientific information was available. In addition to her many short pieces that explode gardening myths (and which have been collected in two volumes by the UW Press), she is also the author of How Plants Work, a sublimely accessible explanation of plant growth and development, health, and photosynthesis. Her free Extension publication on scientific literacy for citizen scientists is a must read in an era of conspiracy folklore gone wild and is used in courses on the philosophy of science.

When we return to normal, Chalker-Scott said, I hope people dont give up gardening. When youre able to understand the science, you dont get frustrated and you dont waste money.

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Gardening with Native Plants book inspires perennial passions | WSU Insider | Washington State University - WSU News

New pathways in plants and microbes

Plants and microbes have interacted through evolution in ways that shaped diversity and helped plants colonize land. Delaux and Schornack review how insights from a range of plant and algal genomes reveal sustained use through evolution of ancient gene modules as well as emergence of lineage-specific specializations. Mosses, liverworts, and hornworts have layered innovation onto existing pathways to build new microbial interactions. Such innovations may be transferrable to crop plants with an eye toward building a more sustainable agriculture.

Science, this issue p. eaba6605

Microbial interactions have shaped plant diversity in terrestrial ecosystems. By forming mutually beneficial symbioses, microbes helped plants colonize land more than 450 million years ago. In parallel, omnipresent pathogens led to the emergence of innovative defense strategies. The evolution of plant-microbe interactions encompasses ancient conserved gene modules, recurrent concepts, and the fast-paced emergence of lineage-specific innovations. Microbes form communities on the surface or inside plant tissues and organs, and most intimately, microbes live within single plant cells. Intracellular colonization is established and controlled in part by plant genes that underpin general cell processes and defense mechanisms. To benefit from microbes, plants also evolved genetic modules for symbiosis support. These modules have been maintained despite the risk of getting hijacked by pathogens.

The hundreds of land plant and algal genomes that are now available enable genome-wide comparisons of gene families associated with plant immunity and symbiosis. Reconstruction of gene phylogenies and large-scale comparative phylogenomic approaches have revealed an ancient subset of genes coevolving with the widespread arbuscular mycorrhiza symbiosis, the most ancient plant intracellular symbiosis, and with other types of more recently evolved intracellular symbioses in vascular and nonvascular plants. Intercellular symbiotic interactions formed with cyanobacteria or ectomycorrhizal fungi seem to repeatedly evolve through convergent, but not necessarily genetically conserved, mechanisms. Phylogenetic analyses revealed occurrence of candidate disease-resistance genes in green algae, as well as orthologs of flowering plant genes involved in symbiosis signaling and sensing microbial patterns. Yet, more research is needed to understand their functional conservation.

The extent to which conserved symbiosis genes also fulfill often opposing roles during pathogen-plant interactions is being explored through studies of pathogen infections in plants capable of supporting symbiotic relationships. The development of plant-microbe systems in genetically tractable species covering the diversity of land plant lineagesincluding angiosperms and bryophytes, such as the liverwort Marchantia polymorphamakes it possible to test hypotheses that emerge from phylogenetic analyses, linking genetic and functional conservation across land plants. Studies in bryophytes illustrate the range of possibilities for pathogen management: ancient genes, such as membrane receptors that perceive fungus-derived chitin; pathways with bryophyte cladespecific components, such as phenylpropanoid-derived auronidin stress metabolites; and jasmonate-like hormonal signaling for immunity.

Only a few plant-microbe interactions have been studied in depth, and those in only a few land plant lineages. Future investigations of interactions occurring across the diversity of plants may unravel new types of symbiotic or pathogenic interactions. The occurrence of microbe-sensing genes in streptophyte algae, harboring the closest algal relative to land plants, suggest the existence of overlooked and potentially ancient symbiotic associations. Genetically tractable plant-microbe model systems in diverse streptophyte algae, hornworts, liverworts, ferns, and the so far unsampled diversity of seed plants will enable dissection of the spectrum of molecular mechanisms that regulate the breadth of interactions occurring in plants. The actual function of the symbiotic genes present in bryophyte genomes also remains to be determined. Furthermore, our understanding of plant-microbe interactions will be enriched by more often combining evolutionary concepts with mechanistic studies. More efforts are needed to decipher the molecular changes that have enabled the emergence of new interactions, signaling pathways, and enzymatic specificities to support symbiosis and to protect against pathogens. Microbes manipulate plant processes, and complementary microbial studies are key to gaining a complete picture of plant-microbe evolution. Knowing the rules of engagement between distantly related plants and their microbes then helps genetic transplantation approaches into crops and the orthogonal engineering of bioprocesses aimed at achieving quantitative resistance against pathogens, improving phosphate uptake, or establishing nitrogen-fixing associations for efficient use in sustainable agriculture.

Some pathogens such as oomycetes are able to infect a wide range of extant plant lineages, including bryophytes (left), and plant pathogen interactions often evolve at a fast pace. By contrast, some symbiotic interactions that look exactly as they do today can be found in the most ancient land plant fossils, here depicted as an illustration of the Rhynie chert fossil plant Aglaophyton major (right). Still, both types of plant-microbe interactions feature evolutionarily ancient as well as rapidly evolving aspects. Extending plant-microbe studies across diverse groups of plant lineages has enriched our understanding of these processes and their evolution.

During 450 million years of diversification on land, plants and microbes have evolved together. This is reflected in todays continuum of associations, ranging from parasitism to mutualism. Through phylogenetics, cell biology, and reverse genetics extending beyond flowering plants into bryophytes, scientists have started to unravel the genetic basis and evolutionary trajectories of plant-microbe associations. Protection against pathogens and support of beneficial, symbiotic, microorganisms are sustained by a blend of conserved and clade-specific plant mechanisms evolving at different speeds. We propose that symbiosis consistently emerges from the co-option of protection mechanisms and general cell biology principles. Exploring and harnessing the diversity of molecular mechanisms used in nonflowering plant-microbe interactions may extend the possibilities for engineering symbiosis-competent and pathogen-resilient crops.

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Plant evolution driven by interactions with symbiotic and pathogenic microbes - Science Magazine

Job descriptionThe Centre for Stem Cells & Regenerative Medicine is located in Guys Hospital.

It is internationally recognized for research on adult and pluripotent stem cells and is a focus for cutting-edge stem cell research currently taking place across the College and its partner NHS trusts, as part of Kings Health Partners. Through the Centre, Kings aims to drive collaboration between scientists and clinicians to translate the potential of stem cells into clinical reality for patients.Applications are invited for a postdoctoral researcher funded as part of the PIs Wellcome Clinical Fellowship, and will work with a dynamic group of scientists focussed on reproductive biology, early embryonic development and the causes of infertility. The post holder will contribute to the regenerative medicine theme and will be involved in the generation and processing of single cell experiments using a variety of techniques.This is an exciting opportunity following our recent work (Sangrithi et al. 2017, Dev Cell & Lau et al. 2020, Dev Cell). The project aims to discover the function of genes on the X-chromosome in male germline stem cells (spermatogonia) and their role in idiopathic and sex chromosome aneuploidy associated infertility. We aim to understand physiological gene regulatory networks functional in spermatogonial stem cells using a combination of single-cell methods, to explain how perturbation in X-gene dosage in SSCs may cause infertility. The postholder will also identify and validate candidate disease bio-markers.

The post holder will be working in Mahesh Sangrithi's group.This post will be offered on an a fixed-term contract until 05/04/2026This is a full-time post - 100% full time equivalent

Key responsibilities Carry out world class research. Are adept at working in a wet lab setting with experience in designing and executing experiments. Familiarity in single cell work nucleic acid manipulation is desirable Communicate results effectively in writing and orally Contribute to publications arising from the research projects Keep clear and up-to-date records of work Attend and present at seminars, journal clubs and conferences Contribute to collaborative atmosphere of the department Share skills by training others Comply with all relevant safety legislation to ensure a safe working environment Take part in public engagement activities To support grant writing, for maintaining the continual research in this domain, e.g. Fellowships Post holder will be expected to plan and prioritise their own workload, with competing and shifting priorities under pressure of deadlinesThe above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria PhD awarded in the biological sciences Excellent general knowledge of molecular biology Knowledge of cell biology Knowledge of flow cytometry Relevant postdoctoral experience Experience in a molecular biology research lab Excellent record keeping / attention to detail Organized and systematic approach to research Pro-active, enthusiastic, positive attitude Self-motivated, with the ability to work under pressure & to meet deadlines Keen interest in infertility and regenerative medicine Ability to think strategically

Desirable criteria Understanding of the biology of germ cells and embryo development Previous experience in working with the laboratory mouse ES cell culture experience General knowledge of computational tools for single cell RNAseq Ability to make collaborative and independent decisions*Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.Further informationABOUT THE SCHOOLThe School of Basic & Medical Biosciences is led by Professor Mathias Gautel and comprises five departments with a wide range of expertise and interests. Using a bench to bedside approach, the School aims to answer fundamental questions about biology in health and disease and apply this to the development of new and innovative clinical practise, alongside providing a rigorous academic programme for students.DepartmentsThe Centre for Human & Applied Physiological Sciences (CHAPS) uses an integrative and translational research approach focusing on fundamental questions about human physiological function in health and disease to explore 3 research themes: skeletal muscle & aging, sensory-motor control & pain and aerospace & extreme environment adaptation.The Centre for Stem Cells & Regenerative Medicine focuses on cutting-edge stem cell research, how stem cells interact with their local environment and how these interactions are important for developing effective cell therapies in the clinic.The Department of Medical & Molecular Genetics uses cutting-edge technologies and analysis techniques to explore the mechanistic basis of disease, improve diagnostics and understand the epigenetic mechanisms of gene regulation and RNA processing, working from whole population level to complex and rare disease genomesThe Randall Centre of Cell & Molecular Biophysics takes a multi-disciplinary approach at the interface of Biological and Physical Sciences to explore the underlying mechanisms behind common diseases.St Johns Institute of Dermatology seeks to improve the diagnosis and management of severe skin diseases, through a better understanding of the basic pathogenetic mechanisms that cause and sustain these conditions focussing on cutaneous oncology, genetic skin disorders, inflammatory & autoimmune skin disorders, and photomedicine.About the Department of Centre for Stem Cells & Regenerative MedicineThe Centre for Stem Cells & Regenerative Medicine is led by Professor Fiona Watt, whos laboratory comprises approximately 30 research staff and visiting scientists and is internationally recognised for research on adult and pluripotent stem cells. Along with Professor Watts group there are nine other research groups operating at the Centre, bringing the total number of staff to approximately 80 people.Research at the Centre is focused on how stem cells interact with their local environment, or niche. We believe that an understanding of these interactions is important for developing effective cell therapies in the clinic. Located on the Guys Hospital campus, the Centre acts as a focus for cutting-edge stem cell research taking place across the College and its partner NHS Trusts, as part of Kings Health Partners. To facilitate collaborations within Kings and with external partners, we have opened a Stem Cell Hotel where researchers can access specialist equipment and technical support to study stem cell behaviour at single cell resolution. We also host an international seminar series and run the Stem Cells @ Lunch seminar series to share ideas and unpublished data. Our researchers are committed to public engagement and take part in diverse outreach events.Detailed information about the Centre for Stem Cells & Regenerative medicine can be found in the link below:http://www.kcl.ac.uk/lsm/research/divisions/gmm/departments/stemcells/index.aspx

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Research Associate in Stem Cells and Regenerative Medicine job with KINGS COLLEGE LONDON | 246711 - Times Higher Education (THE)

AURORA, Colo. (KDVR) The novel coronavirus can rapidly mutate inside of compromised patients and give way to new and more dangerous variants, according to new research from a University of Colorado School of Medicine scientist.

David Pollock, a professor of biochemistry and molecular genetics, co-authored the research in the journal Nature.

He studied a patient in his 70s who had COVID-19 and cancer. In just weeks, the virus mutated multiple times and variants that survived were the strongest and most dangerous.

Its allowing for a much more rapid accumulation of mutationsthan if they go on to infect other people, Pollock said.

In the case of the patient Pollock studied, who ultimately died, the variants were not allowed to escape and infect others. But in other cases the variants do. This has most likely led to the more infectious and possibly more harmful variants in the United Kingdom, South Africa and Brazil.

This is like a pandemic in a pandemic, Pollock said. These are spreading amongst the people who are infected.

These variants are also affecting the COVID-19 vaccine. This is most notable with the Johnson & Johnson vaccine, which went through clinical trials later than the vaccines currently approved.

The vaccine was 72% effective in the United States, but just 58% effective in South Africa, where a variant was running rampant.

The worry and the concern is that the vaccines will be less effective, Pollock said. Its much better to take the vaccine. Youre much (more) likely to be better off if youre protected against the old virus.

Pollock said one way to get ahead of the variants is to do more genome sequencing. Hes now pushing the state to do that.

See original here:
More needs to be done to find and fight COVID-19 variants, says Colorado researcher - FOX 31 Denver

Photo: Michael Behe discusses Biological Truth & Myth: Insights from the Foundation of Life" (screenshot).

Last year I wrote an article here at Evolution News titled Harvard Molecular Geneticist Vindicates Michael Behes Main Argument in Darwin Devolves. I discussed a 2020 paper by Andrew Murray in the journal Current Biology. That paper stated:

In laboratory-based experimental evolution of novel phenotypes and the human domestication of crops, the majority of the mutations that lead to adaptation are loss-of-function mutations that impair or eliminate the function of genes rather than gain-of-function mutations that increase or qualitatively alter the function of proteins.

Murrays paper vindicated Behes thesis which also argued that random mutation and natural selection are in fact fiercely devolutionary. That is since mutation easily breaks or degrades genes, which, counterintuitively, can sometimes help an organism to survive, so the damaged genes are hastily spread by natural selection. (Darwin Devolves, p. 10) He continues:

Darwinian evolution proceeds mainly by damaging or breaking genes, which, counterintuitively, sometimes helps survival. In other words, the mechanism is powerfully devolutionary. It promotes the rapid loss of genetic information. [p. 37, emphasis in original.]

Now Behe has been vindicated again by a 2021 paper in Nature Heredity, which agrees that loss-of-function mutations are prevalent in the evolutionary process:

Views on loss-of-function mutations those abolishing a genes biomolecular activity have changed considerably over the last half century. Early theories of molecular evolution that emerged during the 1960s and 1970s saw little potential for loss-of-function mutations to contribute to adaptation (Maynard Smith1970). Except in the case of inactivated gene duplicates, nonfunctional alleles were often assumed to be lethal, with adaptation being generally regarded as a process explained only by the fixation of single, mutationally rare alleles that improved or altered a genes function (Orr2005). Only relatively recently, through discoveries enabled by the availability of molecular sequence data, were alternative views of adaptive loss-of-function alleles formalized, most notably with the less is more ideas proposed by Olson (1999). Classical paradigms of molecular evolution had by that time been challenged, for example, by evidence that natural loss-of-function variants of CCR5 lead to reduced HIV susceptibility in humans (Libert et al.1998). Discoveries during the subsequent two decades have continued to support the idea that loss of function contributes to adaptation (Murray2020), with cases of adaptive or beneficial loss of function being discovered across diverse organisms, genes, traits, and environments.

You might notice that the final citation in the quote above is to Murray (2020) thats the same Andrew Murray mentioned above, the Harvard geneticist I wrote about last year who similarly proposed that evolutionary adaptations frequently proceed by breaking functionality at the molecular level. Professor Murrays paper was appropriately cited, but unfortunately this 2021 paper conspicuously avoids citing Behes 2010 paper in the respected Quarterly Review of Biology, Experimental evolution, loss-of-function mutations, and the first rule of adaptive evolution. There, Behe makes similar arguments. Nor does it cite Behes 2019 book Darwin Devolves. But its enough to accept the vindication even if we dont get the citation.

Citing away to the relevant literature (excluding Behe), this 2021 paper continues:

Today, reductive genome evolution is viewed as a powerful force of adaptation (Wolf and Koonin 2013) and gene loss is considered an important source of adaptive genetic variation (Albalat and Caestro 2016; Murray 2020). While the existence of adaptive loss of function is no longer seriously disputed, the assumed maladaptive nature of loss of function from early theories can persist in the language of population genetics such as in the continued use of deleterious as a synonym for loss-of-function (Moyers et al. 2018). he existence of a category of alleles distinguished by a derived loss of biochemical function has been described by various names: amorphic (Muller 1932), loss-of-function (Jones 1972), nonfunctional (Nei and Roychoudhury 1973), knockout (Kulkarni et al. 1999),null (Engel et al. 1973), pseudogene (Jacq et al. 1977), or simply gene loss (Zimmer et al. 1980). Total gene loss is the most obvious case of loss of function. Comparisons of gene content between distantly related species have revealed considerable evidence for adaptation via complete deletion of genes or even entire sets of functionally related genes (Wang et al. 2006; Blomme et al. 2006; Will et al. 2010; McLean et al. 2011; Griesmann et al. 2018; van Velzen et al. 2018; Sharma et al. 2018; Huelsmann et al. 2019; McGowen et al. 2020; Baggs et al. 2020).

The article goes on to explore various mutational mechanisms which lead to loss of function in genes, and complete gene loss, providing a theoretical basis for Behes thesis:

First principles and empirical evidence indicate that many types of mutations can have effects that are equivalent to total gene loss, and for the purposes of this review, we employ this definition of complete gene losses being functionally equivalent to other loss-of-function mutations such as premature stop codons. However, there is the practical difficulty that these different types of mutations vary in how easily they can be detected and correctly annotated as loss-of-function alleles (Fig. 3). Insertions and deletions that interrupt the reading frame of a protein coding region (frameshift mutations), for example, might be readily classified as loss-of-function alleles because the downstream amino acid sequence will be severely disrupted. Yet a frameshift mutation at the extreme 3 end of a coding region affecting only a few amino acids might be functionally distinct from a frameshift mutation at the extreme 5 end disrupting the entire coding sequence. One simple heuristic to address this ambiguity is a threshold, measured by the portion of the gene affected by functionally disruptive mutations, at which an allele is classified as loss-of-function. This approach can be used to classify premature stop codons, frameshift, splice site disruptions, start loss, and inframe insertions and deletions. In humans (MacArthur et al. 2012; Karczewski et al. 2020) and Arabidopsis thaliana (Monroe et al. 2018; Baggs et al. 2020), loss-of-function mutations affecting only a small fraction (e.g., <10%) of total coding sequence in a gene were ignored when classifying loss-of-function variants.

The paper then explores methods for detecting when loss-of-function has been selected by natural selection:

Loss-of-function alleles were once often held up as a paragon of deleterious genetic variation. Today a more nuanced appreciation for their potential role in adaptation has emerged. This new paradigm inspires investigations into deeper questions about the causes and consequences of adaptation by genetic loss of function. For example: Do species or populations differ in their capacity to adapt via loss of function, and if so, why? Does the high effective mutation rate of loss-of-function alleles lead to bias in the probabilities of different evolutionary outcomes? What is the contribution of adaptive loss of function to the phenomena of antagonistic pleiotropy and reproductive isolation? How does adaptation by loss of function affect long term evolutionary trajectories of populations and future evolvability?

Focus on the last question: What does the prevalence of function-damaging mutations imply for the evolutionary process? This question is an important one, and its one to which Michael Behe, through the lens of intelligent design, has proposed an answer. The answer is essentially that a mechanism that proceeds primarily by breaking molecular features cannot easily account for the origin of new functional biological features at the molecular level. Heres what Behe writes in Darwin Devolves:

From the dawn of life to the present, beneficial degradation has been a constant background theres no way to avoid it. From the beginning the Darwinian mechanism has been self-limiting, capable to an extent of eliminating or modifying preexisting molecular systems and in the process giving rise to new varieties of creatures below the biological classification level of family (described in Chapter 6), but incapable of building functionally complex molecular structures. To explain them, we must look elsewhere. (p. 251)

The literature is looking at the same data that intelligent design proponents are looking at, making similar observations, and asking similar questions. While ID proponents dont always get recognized in the literature for their contributions, a careful analysis nonetheless shows that ID thinking is highly relevant to answering questions that everyone is asking.

Original post:
Vindicated But Not Cited: Paper in Nature Heredity Supports Michael Behe's Devolution Hypothesis - Discovery Institute

Introduction

Tuberculosis (TB) continues to be one of the most important public health problems, causing high morbidity and mortality, primarily in low- and middle-income countries.1 Globally the total TB incidence has declined by an average of 1.6% per year since 2000.1 However, the reduction in the number of extrapulmonary TB (EPTB) cases has been slower, resulting in a proportionate increase in EPTB compared to pulmonary TB (PTB).2 EPTB represented 30% of all case of TB notified in Ethiopia, which is greater than the global average of 16%.1 TB lymphadenitis (TBLN) accounted for 80% of all EPTB cases reported in Ethiopia.3

Multidrug resistant (MDR)-TB, which is defined as being resistant at list for rifampicin (RIF) and isoniazid (INH), remains a public health problem in many parts of the world.1 Globally, half a million people developed MDR/RIF resistant (RIFR)-TB in 2019.1 Ethiopia is one of 14 countries included in all three World Health Organization (WHO) high burden country lists for TB, TB/HIV, and MDR-TB.1 Together with an increasing number of drug resistant TBs around the world, the number of cases of primary MDR-TB with EPTB presentation is also going to rise.4 However, drug resistant EPTB is largely neglected and it does not receive specific attention in international control strategies.5 As a result, drug resistant isolates from EPTB are not well investigated, particularly in low-income countries.

The causative agents of TB are species of the Mycobacterium tuberculosis complex (MTBC) comprising of seven human adopted lineages (Lineage 17) which show biogeographic specificities in that the individual lineages are associated with particular geographic locations.6 Also, the MTBC includes species that are more commonly found in animals, but with zoonotic ability.7 Lineages 2, 3 and 4 are referred to as modern lineages, whereas Lineages 1, 5 and 6 are called ancient. Lineage 7 is phylogenetically localized between ancient and modern lineages and considered as a premodern lineage.6,8,9 Although both modern and ancient lineages exist in Ethiopia, the modern lineages, particularly 4 and 3, are the most prevalent types.10,11

Mycobacterium tuberculosis (M. tuberculosis) is described as a clonal bacterium, with no known plasmid and does not engage in horizontal gene transfer. Consequently, drug resistance in M. tuberculosis is usually mediated by chromosomal mutations and rearrangements.12,13 Molecular studies identied katG and rpoB as major targets conferring resistance of M. tuberculosis to INH and RIF respectively. Also, mutations in the regulatory region of the inhA operon, encoding a putative enzyme involved in mycolic acid biosynthesis, causes overexpression of the InhA protein, leading to INH resistance through a titration mechanism.14,15

Despite low genetic diversity in M. tuberculosis compared to other bacteria, the strain genetic background has been reported to plays a role in the global emergence of drug resistant TB. For instance, Beijing strains that belong to Lineage 2 have been frequently associated with drug resistance.16,17 Therefore, describing drug resistance conferring mutations in M. tuberculosis and their strain diversity circulating in a specific geographical area is important for both biological and epidemiological reasons. Although several studies conducted in Ethiopia assessed drug resistance patterns and genetic diversity of M. tuberculosis isolates from PTB patients, only limited data is available in the same regard from TBLN patients. With this background, this study aims to evaluate gene mutations conferring drug resistance and to further investigate variations among M. tuberculosis strains of TBLN patients.

This study was conducted using M. tuberculosis isolates retrieved from Armauer Hansen Research Institute (AHRI) laboratory biorepository that have been collected between 2016 and 2017 from Bishoftu, Gondar, Mekele and Hawassa in Ethiopia, as part of the Ethiopia Control of Bovine Tuberculosis (ETHICOBOT) study. Isolates were retrieved from culture positive Fine Need Aspirate (FNA) specimens collected from TBLN patients using a convenient sampling method. Clinical and demographic information for each isolate was retrieved from the ETHICOBOT study database using structured data extraction sheets.

RIF and INH resistance conferring mutation was detected using GenoType MTBDRplus VER 2.0. (Hain Life Science GmbH, Nehren, Germany) according to the manufacturers instruction. The test is based on DNA strip technology and has three steps: DNA extraction, amplification, and reverse hybridization. GenoType MTBDRplus VER 2.0 detects the absence and/or presence of wild type (WT) and/or mutant (MUT) DNA sequences within specific regions of three genes: the rpoB gene-gene (coding for the -subunit of the RNA polymerase), for the identification of RIFR; the katG gene (coding for the catalase peroxidase), for high level INH resistance (INHR); and the promoter region of the inhA gene (coding for the NADH enoyl ACP reductase), for low level INHR. GenoType MTBDRplus included eight rpoB WT probes, four rpoB MUT probes in positions of rpoB MUT1 (D516V), rpoB MUT2A (H526Y), rpoB MUT2B (H526D) and rpoB MUT3 (S531L), one katG WT probe, two katG MUT probes with katG MUT1 (S315T1) and katG MUT2 (S315T2), two inhA WT probes and four inhA MUT probes with inhA MUT1 (C15T), inhA MUT2 (A16G), inhA MUT3A (T8C) and inhA MUT3B (T8A). According to the manufacturers recommendations, the missing of a WT probe or presence of a MUT probe were considered as resistant.

Spoligotyping was carried out as described by Kamerbeek et al.18 Spoligotype patterns of each strain were prepared in binary and octal format and entered into spoligotyping database SITVIT2 (http://www.pasteur-guadeloupe.fr:8081/SITVIT2/), which is an updated version of SITVITWEB.19 Strains matching a preexisting pattern in the database were identified with Spoligo International Type (SIT) number, otherwise considered as orphans or new. Run TB-Lineage online tools (http://tbinsight.cs.rpi.edu/run_tb_lineage.html) was used to predict major M. tuberculosis lineages.20 Nomenclature for lineage names and numbers were assigned as proposed previously. For instance, Lineage 1 (Indo Oceanic; IO), Lineage 3 (East African-Indian; EAI), Lineage 4 (Euro-American; EA) and Lineage 7 (Ethiopian).21,22

Standard operational procedures for all laboratory tests were employed uniformly throughout the study. PCR was carried out in three separate rooms for DNA extraction, PCR mix preparation and amplification using dedicated pipettes and sterile tips. Furthermore, DNA from M. bovis Bacille Calmette-Guerin and M. tuberculosis H37Rv were used as positive controls while DNA free water from Qiagen was used as a negative control in each batch of the test.

Data were double entered to an Excel file format and statistical analysis was performed using SPSS version 20 (IBM Corp, Armonk, NY, USA). Descriptive statistics were used to depict the demographic variables. The Fisher exact was calculated to test the association between drug resistant conferring mutation and specific lineages of M. tuberculosis isolates. P-value 0.05 was considered statistically significant.

Ethical approval was obtained from the AHRI/ALERT Ethics Review Committee. Since the entire repository data were anonymized, no personal identifiers were collected during data retrieval.

A total of 91 M. tuberculosis isolates obtained from TBLN patients were included in this study, of which 54 (59.3%) were from females and 37 (40.7%) from males. The patients mean age was 32 years with a range of 976 years (Table 1). Of the 91 isolates included in this study, 35 (38.5%), 27 (29.7%), 21 (23.1%) and 8 (8.8%) were collected from Bishoftu, Gondar, Mekele and Hawassa, respectively.

Table 1 Demographic Characteristics of Study Participants from Different Places in Ethiopia, 20162017

Of 91 isolates tested for GenoType MTBDRplus VER 2.0, mutations conferring resistance to RIF and INH were observed in two (2.2%) and six (6.6%) isolates, respectively. Two (2.2%) of them were MDR isolates. Of isolates with resistant mutations, two (2.2%) were in the rpoB gene, four (4.4%) were in the katG gene and two (2.3%) were in the inhA promoter region. In two RIFR isolates, mutation was observed at codon S531L indicated by missing of rpoB WT8 probe with gain in rpoB MUT3 probes. Four of the six INHR isolates had a katG mutation. In three of these isolates, the mutation was observed at codon S315T1 indicated by absence of KatG WT with gain in katG MUT1 whereas one isolate had a mutation at S315T2 indicated by the absence of KatG WT with gain of KatG MUT2. Mutations in the inhA promoter gene occurred in two INHR isolates. One of these isolates had a mutation at codon C15T which was indicated by the omission of inhA WT1 and with the presence of the inhA MUT1 band. In one isolate inhA MUT1 band developed without missing the WT probe (Table 2). All drug resistant isolates were from treatment naive TBLN patients.

Table 2 Mutations Identified in Isoniazid and Rifampicin Resistant M. tuberculosis Strains

Among the 91 spoliogotyped isolates, 82 (90.1%) were classified into 28 different spoligotyping patterns according to the SITVIT2 database. The remaining 9 (9.9%) isolates were not registered in the database and thereby seen as new or orphans strains. The dominating identified SITs were SIT25, SIT149 and SIT53, each consisting of 19 (20.9%), 11 (12.1%) and 9 (9.9%) isolates, respectively (Figure 1).

Figure 1 Spoligotypes and major lineage classifications of clinical M. tuberculosis strains isolated from TBLN patients in different places in Ethiopia, 20162017.

Lineage 3 (EAI) was the most prevalent lineage in Gondar (18/27, 66.7%) and Mekele (11/21, 52.3%), whereas Lineage 4 (EA) was the most prevalent lineage in Bishoftu (27/35, 77.1%) and Hawassa (7/8, 87.5%). Two strains belonging to Lineage 1 (IO) were isolated in this study, both of them were from Mekele (SIT726). Furthermore, two Lineage 7 (Ethiopian) isolates were identified, one from Mekele (SIT910) and one from Gondar (SIT1729). Overall, Lineage 3 and Lineage 4 were the most prevalent lineages identified in this study, each accounted for 41.7% (38/91) and 53.8% (49/91), respectively. Whereas Lineage 1 and Lineage 7 were the least prevalent lineages, each accounted for 2.2% of the total isolates (Table 3).

Table 3 M. tuberculosis Lineage Distribution in Different Sample Collection Places in Ethiopia, 20162017

Cluster analysis based on spoligotyping patterns showed that 63 isolates were grouped into 9 clusters; as one cluster consisted of 219 isolates. The clustering rate was 69.2%. Statistically significant different rate of clustering observed between major MTBC lineages (Fishers Exact test = 8.413; P = 0.017) (Table 4).

Table 4 Cluster Distribution Among Different Mycobacterium tuberculosis Lineages

Isolates with drug resistance conferring mutations for any of the anti-TB drugs (RIF or INH), tested for by GenoType MTBDRplus, belonged to Lineage 3 (50%; 3/6) and Lineage 4 (50%; 3/6). However, an association between having anti-TB drug conferring mutation and major M. tuberculosis lineages were not statistically significant (Fisher exact test: 1.355; p > 0.05). Four out of six (66.7%) of the drug resistant isolates in this study belonged to a clustered strain (strains with shared SIT). Out of the three resistant strains of Lineage 3, one MDR-TB isolate with rpoB and KatG mutations was of SIT25, and two INHR isolates with inhA mutation had SIT26 and Orphan spoligotypes, whereas, among the resistant strains of Lineage 4, one MDR-TB isolate with rpoB and KatG mutations was of SIT149, two INHR isolates with a katG mutation were of SIT 50 and SIT 149 (Table 2).

This study presented the magnitude of drug resistance conferring mutation and genetic diversity of M. tuberculosis strains that cause TBLN in Ethiopia. Among the 91 isolates included in this study, mutations conferring resistance to RIF, INH, and to both of these drugs (MDR-TB), were observed in 2 (2.2%), 6 (6.6%), and 2 (2.2%) isolates, respectively. 2.2% MDR prevalence in this study was comparable with previous studies reported from Ethiopia among TBLN (14%)2325 and PTB patients (13%).2527. The problem of MDR in TBLN patients should not be ignored and early diagnosis of drug resistance is crucial to avoid the devastating effect of MDR TB.

The two RIFR isolates identified in this study contained the S531L mutation in the rpoB gene, which is the most frequently reported rpoB mutation in the Ethiopian strains,23,2830 indicating the possible transmission of strains with similar types of mutations in the community. However, mutations at other codons including H526D and D516V had also been reported among RIFR isolates.2831 Both RIFR strains in this study were INHR. Mono resistance to RIF is quite rare and almost all RIFR strains were also resistant to other drugs, especially to INH, which is why RIFR is considered as a surrogate marker for MDR-TB.15

Resistance to INH is frequently associated with a mutation at two genes; katG and inhA. In this study, 67% (4/6) of INHR isolates had a katG gene mutation at codon S315T. In contrast to this, 100% frequency of KatG mutation at codon S315T among INHR isolates had been reported from Ethiopia.23,28,30,32 Moreover, in the current study, gene mutations attributed to low level INHR mainly caused by the mutations in the promoter region of inhA gene were also observed. Such mutations were more frequent in our study (43%, 3/7) than the 1012% reported by other studies conducted in Ethiopia,29,33 in Pakistan (17%),34 and in Switzerland (23%).35 Mutations in inhA gene not only causes resistance to INH but also to the structurally related drug ethionamide, which shares the same target.14 Of the two isolates with inhA mutation, one of them had a mutation at C15T, whereas the other one had inhAMUT1 without mutation on the corresponding WT probe indicating heteroresistant isolates, ie concomitant infection with drug-resistant and drug-susceptible strains. TB infection with a heteroresistant M. tuberculosis population can be caused by infection with two different strains or the splitting of a single strain into susceptible and resistant organisms through microevolution.36,37 The relevance of heteroresistant TB should not be underestimated especially in highly endemic areas like Ethiopia, where there is a chance of co-infection with different M. tuberculosis strains with different resistant conferring mutations.

The M. tuberculosis population structure in this study was highly diverse and comprised of 28 different SITs and nine orphans or new strains. It is not unexpected, considering the samples are collected from different regions of the country. Lineage 3 and Lineage 4 were the most prevalent lineages identified in this study, each accounted for 41.7% and 53.8%, respectively. Similar patterns of lineage distribution were reported from different regions of Ethiopia among EPTB3841 and PTB patients.26,30 Likewise, a study that analyzed the distribution of genotypes among PTB and TBLN patients in Ethiopia, reported a similar distribution of genotypes between the two manifestations of the disease.8 This may indicate the absence of pathogen-specific genetic factors associated with the high rate of TBLN in Ethiopia and also suggested a similar route of PTB and TBLN transmission in the community. Lineage 4 has a broad distribution in Europe and America, Africa and the Middle-East whereas Lineage 3 has a relatively narrow distribution occurring in East Africa and Central and South Asia.9

Lineage 1 and Lineage 7 were the least prevalent lineages in this study, each accounted for 2.2% of the 91 TBLN isolates, which is in line with the overall relatively low prevalence of these lineages in Ethiopia.10,11 Lineage 1 is found in areas around the Indian Ocean and the Philippines.9 The Lineage 1 isolates (two isolates) in this study were isolated from Mekele TBLN patients. Previously, Lineage 1 was also reported from Southern,8,42 Central39 and North Ethiopia.32,43 The two Lineage 7 isolates identified in this study were isolated from Mekele and Gondar TBLN patients. This is the newly identified lineage initially reported in higher frequency from Woldia in Northern Ethiopia.8 Since then, it has been reported from different regions of the country.38,40,44,45 Lineage 7 has also been reported among Ethiopian immigrants in Djibouti and the Netherlands.46,47 The reason why Lineage 7 is restricted to native Ethiopians and Ethiopian immigrants is not yet well understood but it has been indicated that Lineage 7 has a lower rate of progression towards disease relative to other lineages, with subsequent out competition by other M. tuberculosis lineages.44 That may explain the geographical restriction of Lineage 7 to Ethiopia. Lineage 7 has contributed to the rejection of the virgin soil hypothesis of human TB in sub-Saharan Africa. According to virgin soil hypothesis, TB in the African region was due to European contact during the colonial period as it was originally free of TB.48

In our study, the overall clustering rate (strains with shared SIT) was 65.6% which is in line with other studies conducted in Ethiopia.8,26,41,49 A high rate of clustering maybe indicates active transmission of the disease and an ineffective TB control programme in the country. However, the low discrimination power of spoligotyping should be considered.50

The majority (4/6, 66.7%) of isolates with drug resistant conferring mutations in this study belonged to clustered strains, suggesting the possibility of transmission of drug resistant isolates between patients in the country. Moreover, all drug resistant isolates identified in the current study were from treatment of nave TBLN patients. That supports exposure of the patients to drug resistant M. tuberculosis strains in the community, rather than susceptible strains becoming resistant during the TB treatments. This needs to be carefully considered to prevent the spread of drug resistant clones in the country. Of the six isolates with drug resistant conferring mutations, two (33%) of them were SIT 149 whereas the rest were SIT 25, SIT 26, SIT 50 and one orphan strain. The high frequency of SIT149 among drug resistant M. tuberculosis isolates has been previously reported in Ethiopia.51,52 However, Bereket et al indicated that the observed association between SIT149 and the development of drug resistance may not necessarily indicate that the stains are prone to be drug resistant but could rather be association consequences of their high prevalence in the population.25

No significant associations were found between a particular lineage and any drug resistant conferring mutation. However, this might have been due to the low sample size. Apart from results shown for Lineage 2,16,17 the association between different M. tuberculosis lineages and TB drug resistance is rather inconsistent. For instance, Biadglegne et al40 and Tadesse et al38 showed a significant association between drug resistance and Lineage 3, whereas Amir et al found an association between Lineage 4 and drug resistance conferring mutations.32 In contrast, other studies did not find associations between the genotype of M. tuberculosis isolates and their drug resistance pattern.53,54 This shows that there is uncertainty on the strain-specific propensity for the acquisition of drug resistance conferring mutation among M. tuberculosis isolates. More work needs to be done to define whether some M. tuberculosis genotypes are more prone than others to develop drug resistance.

Overall, although the sensitivity of the GenoType MTBDRplus assay to detect strains with a novel mutation or gene mutation outside the resistance determining region is limited, the present study demonstrated the feasibility of estimating the magnitude of gene mutations conferring drug resistance and genetic diversity of drug resistant M. tuberculosis isolates in TBLN patients. Lineage 3 and Lineage 4 were the most prevalent lineage types identified in this study with high clustering rates of SIT 25, SIT149 and SIT 53. A drug resistant conferring mutation was detected among clustered strains, which could suggest clonal resistant strains transmission in the community. However, the tool we used to characterize the different M. tuberculosis strains, spoligotyping, is prone to convergent evolution and has low resolution power for cluster analysis. This warrants the need for future studies with a better tool of discrimination power like whole-genome sequencing (WGS) to understand the transmission dynamics of drug resistant TB and strengthen the control programs of TBLN in Ethiopia.

We would like to thank study participants for taking part in the study and all members of the ETHICOBOTS project who had a great contribution to the success of this study. The members of the ETHICOBOTS consortium are: Abraham Aseffa, Adane Mihret, Bamlak Tessema, Bizuneh Belachew, Eshcolewyene Fekadu, Fantanesh Melese, Gizachew Gemechu, Hawult Taye, Rea Tschopp, Shewit Haile, Sosina Ayalew, Tsegaye Hailu, all from the Armauer Hansen Research Institute, Ethiopia; Rea Tschopp from the Swiss Tropical and Public Health Institute, Switzerland; Adam Bekele, Chilot Yirga, Mulualem Ambaw, Tadele Mamo, Tesfaye Solomon, all from the Ethiopian Institute of Agricultural Research, Ethiopia; Tilaye Teklewold from the Amhara Regional Agricultural Research Institute, Ethiopia; Solomon Gebre, Getachew Gari, Mesfin Sahle, Abde Aliy, Abebe Olani, Asegedech Sirak, Gizat Almaw, Getnet Mekonnen, Mekdes Tamiru, Sintayehu Guta, all from the National Animal Health Diagnostic and Investigation Centre, Ethiopia; James Wood, Andrew Conlan, Alan Clarke, all from Cambridge University, United Kingdom; Henrietta L. Moore and Catherine Hodge, both from University College London, United Kingdom; Constance Smith at University of Manchester, United Kingdom; R. Glyn Hewinson, Stefan Berg, Martin Vordermeier, Javier Nunez-Garcia, all from the Animal and Plant Health Agency, United Kingdom; Gobena Ameni, Berecha Bayissa, Aboma Zewude, Adane Worku, Lemma Terfassa, Mahlet Chanyalew, Temesgen Mohammed, Yemisrach Zeleke, all from Addis Ababa University, Ethiopia.

This work was supported by Armauer Hansen Research Institute (AHRI) and the Biotechnology and Biologic Sciences Research Council, the Department for International Development, the Economic & Social Research Council, the Medical Research Council, the Natural Environment Research Council and the Defence Science & Technology Laboratory, under the Zoonoses and Emerging Livestock Systems (ZELS) program, ref: BB/L018977/1.

The authors report no conflicts of interest for this work.

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