%0 Journal Article %J PLOS Global Public Health %D 2023 %T Rethinking global digital health and AI-for-health innovation challenges %A Andrew Farlow %A Alexander Hoffmann %A Girmaw Abebe Tadesse %A Deogratias Mzurikwao %A Rob Beyer %A Darlington Akogo %A Eva Weicken %A Tafadzwa Matika %A MaryJane Ijeoma Nweje %A Watu Wamae %A Sako Arts %A Thomas Wiegand %A Colin Bennett %A Farhat, Maha R. %A Matthias I. Groeschel %B PLOS Global Public Health %G eng %U https://doi.org/10.1371/journal.pgph.0001844 %0 Journal Article %J The Lancet Infectious Diseases %D 2023 %T Clinical implications of molecular drug resistance testing for Mycobacterium tuberculosis: a 2023 TBnet/RESIST-TB consensus statement by Dr Jose Dominguez. %A Jose Dominguez %A Martin J. Boeree %A Dumitru Chesov %A Francesca Conradie %A Vivian Cox %A Keertan Dheda %A Andrii Dudnyk %A Farhat, Maha R. %A Gagneux, Sebastien %A Martin P. Grobusch %A Matthias Groeschel %A Lorenzo Guglielmetti %A Irina Kontsevaya %A Berit Lange %A Frank van Leth %A Lienhardt, Christian %A Anna M. Mandalakas %A Florian Maurer %A Matthias Merker %A Paolo Miotto %A Barbara Molina-Moya %A Florence Morel %A Niemann, Stefan %A Nicolas Veziris %A Andrew Whitelaw %A Charles R. Horsburgh %A Christoph Lange %B The Lancet Infectious Diseases %8 2023 %G eng %U https://www.sciencedirect.com/science/article/abs/pii/S1473309922008751?dgcid=author %0 Journal Article %J American Society for Microbiology %D 2022 %T Optimizing DNA Extraction from Pediatric Stool for Diagnosing Tuberculosis and Use in Next Generation Sequencing Applications %A Ness, T %A Meiwes, L %A Kay, A %A Mejia, R %A Christoph Lange %A Farhat, Maha R %A Anna Mandalakas %A DiNardo, A %B American Society for Microbiology %G eng %U https://journals.asm.org/doi/10.1128/spectrum.02269-22 %0 Web Page %D 2022 %T Mycobacterium tuberculosis Infection: Policy Gaps and Research Breakthroughs %A Tara Ness %A Andrew DiNardo %A Farhat, Maha R. %B Pathogens %G eng %U https://www.mdpi.com/2076-0817/11/11/1343 %0 Journal Article %J Clin Infect Dis. %D 2022 %T Whole Genome Sequencing Assessing Impact of Diabetes Mellitus on Tuberculosis Mutations and Type of Recurrence in India %A Mave, V %A L. Chen %A Ranganathan, U %A Kadam, D %A Vishwanathan, V %A Lokhande, R %A Kumar, S. %A Kagal, A %A Pradhan, N %A Yogendra Shivakumar, S %A Paradkar, M %A Deshmukh, S %A Tornheim, J %A Kornfeld, H %A Farhat, Maha R %A A. Gupta %A Padmapriyadarsini, C %A Gupte, N %A Golub, J %A Mathema, B %A Kreiswirth, Barry N %B Clin Infect Dis. %G eng %U https://academic.oup.com/cid/article-abstract/75/5/768/6497515?redirectedFrom=fulltext&login=false %0 Journal Article %J medRxiv %D 2022 %T Demographic and Viral-Genetic Analyses of COVID-19 Severity in Bahrain Identify Local Risk Factors and a Protective Effect of Polymerase Mutations. %A Koch, Evan %A Du, Justin %A Dressner, Michelle %A Alwasti, Hashmeya Erahim %A Zahra Al Taif %A Shehab, Fatima %A Mohamed, Afaf %A Ghanem, Amjad %A Haghighi, Alireza %A Sunyaev, Shamil %A Farhat, Maha R %B medRxiv %G eng %U https://doi.org/10.1101/2022.08.13.22278740 %0 Journal Article %J medRxiv %D 2022 %T Host-pathogen co-adaptation shapes susceptibility to infection with Mycobacterium tuberculosis %A Matthias I Gröschel %A Francy J. Pérez-Llanos %A Roland Diel %A Vargas Jr, Roger %A Vincent Escuyer %A Kimberlee Musser %A Lisa Trieu %A Jeanne Sullivan Meissner %A Knoor, J %A Don Klinkenberg %A Peter Kouw %A Susanne Homolka %A Wojciech Samek %A Mathema, Barun %A van Soolingen, Dick %A Niemann, Stefan %A Shama Ahuja %A Farhat, Maha R %B medRxiv %G eng %U https://www.medrxiv.org/content/10.1101/2022.08.04.22278337v1 %0 Journal Article %J Nature Communications %D 2022 %T A convolutional neural network highlights mutations relevant to antimicrobial resistance in Mycobacterium tuberculosis. %A Green, A.G %A Yoon, Chang Ho %A Chen, Michael %A Ektefaie, Yasha %A Fina, Mack %A Freschi, Luca %A Matthias I. Groschel %A Kohane I %A Beam, Andrew %A Farhat, Maha R %B Nature Communications %V 13 %G eng %U https://doi-org.ezp-prod1.hul.harvard.edu/10.1038/s41467-022-31236-0 %N 3817 %0 Journal Article %J Eur Respir J. %D 2022 %T Updating the approaches to define susceptibility and resistance to antituberculosis agents: implications for diagnosis and treatment. %A Claudio Koser et al including Maha Farhat and Roger Vargas %B Eur Respir J. %G eng %U https://erj.ersjournals.com/content/59/4/2200166 %0 Journal Article %J ISCB %D 2022 %T Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome %A Marin, M %A Vargas, R %A Harris, M. %A Epperson, L %A Jeffrey, B %A Durbin, D %A Strong, M %A Salfinger, M %A Iqbal, Z %A Akhundova, I %A Vashakidze, S %A Crudu, V %A Rosenthal, A %A Farhat, Maha R %B ISCB %V 38 %P 1781–1787, %G eng %U https://academic.oup.com/bioinformatics/article-abstract/38/7/1781/6502279?redirectedFrom=fulltext %N 7 %0 Journal Article %J International Journal of Tuberculosis and Lung Disease %D 2022 %T Management of childhood MDR-TB in Europe and Central Asia: report of a Regional WHO meeting. %A Matthias I. Groschel %A Boom, Van Den %A Dixit, A %A Skrahina, A %A Dodd, P.J. %A Migliori, G.B %A Seddon, J.A. %A Farhat, Maha R %B International Journal of Tuberculosis and Lung Disease %V 26 %G eng %U https://www.ingentaconnect.com/content/iuatld/ijtld/2022/00000026/00000005/art00010;jsessionid=155bb6g04i2gn.x-ic-live-03 %N 5 %0 Journal Article %J American Journal of Respiratory and Critical Care Medicine %D 2022 %T Tuberculosis Pathways to Care and Transmission of Multidrug Resistance in India. %A Atre, Sachin %A Jagtap, J %A Faqih, Mujtaba %A Dumbare, Yogita %A Sawant, T %A Ambike, S %A Bhawalkar, J %A Bhawalkar, Sandeep %A Jogewar, P %A Adkekar, J %A Hodgar, B %A Jadhav, V %A Mokashi, N %A Golub, J %A Dixit, V %A Farhat, Maha R %B American Journal of Respiratory and Critical Care Medicine %V 205 %G eng %U https://www.atsjournals.org/doi/10.1164/rccm.202012-4333OC %N 2 %0 Journal Article %J medRxiv %D 2022 %T Modern lineages of Mycobacterium tuberculosis were recently introduced in western India and demonstrate increased transmissibility %A Dixit, A %A Kagal, A %A Ektefaie, Yasha %A Freschi, L %A Karyakarte, K %A Lokhande, R %A Groschel, M %A Tornheim, J %A Gupte, N %A Pradhan, N %A Paradkar, M %A Deshmukh, S %A Kadam, D %A Schito, M %A Engelthaler, D %A A. Gupta %A Golub, J %A Mave, V %A Farhat, Maha R %B medRxiv %G eng %U https://www.medrxiv.org/content/10.1101/2022.01.04.22268645v1 %0 Journal Article %J medRxiv %D 2021 %T Estimation of country-specific tuberculosis antibiograms using genomic data %A Dixit, Avika %A Freschi, Luca %A Vargas R. %A Matthias Groeschel %A Tahseen, Sabira %A Alam, SM Masud %A Kamal, SM Mostofa %A Skrahina, Alena %A Basilio, Ramon %A Lim, Dodge %A Ismail, Nazir %A Farhat, Maha R %B medRxiv %G eng %U https://www.medrxiv.org/content/10.1101/2021.09.23.21263991v1 %0 Journal Article %J Genome Medicine %D 2021 %T Gen TB: A user-friendly genome-based predictor of tuberculosis resistance powered by machine learning %A Groschel M, %A Owens M, %A Freschi L %A Vargas R %A Marin M %A Phelan J, %A Iqbal Z %A Dixit A %A Farhat MR. %X
Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.
We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tuberculosis drugs, respectively. We benchmark GenTB’s predictive performance along with leading TB resistance prediction tools (Mykrobe and TB-Profiler) using a ground truth dataset of 20,408 isolates with laboratory-based drug susceptibility data. All four tools reliably predicted resistance to first-line tuberculosis drugs but had varying performance for second-line drugs. The mean sensitivities for GenTB-RF and GenTB-WDNN across the nine shared drugs were 77.6% (95% CI 76.6–78.5%) and 75.4% (95% CI 74.5–76.4%), respectively, and marginally higher than the sensitivities of TB-Profiler at 74.4% (95% CI 73.4–75.3%) and Mykrobe at 71.9% (95% CI 70.9–72.9%). The higher sensitivities were at an expense of ≤ 1.5% lower specificity: Mykrobe 97.6% (95% CI 97.5–97.7%), TB-Profiler 96.9% (95% CI 96.7 to 97.0%), GenTB-WDNN 96.2% (95% CI 96.0 to 96.4%), and GenTB-RF 96.1% (95% CI 96.0 to 96.3%). Averaged across the four tools, genotypic resistance sensitivity was 11% and 9% lower for isoniazid and rifampicin respectively, on isolates sequenced at low depth (< 10× across 95% of the genome) emphasizing the need to quality control input sequence data before prediction. We discuss differences between tools in reporting results to the user including variants underlying the resistance calls and any novel or indeterminate variants
GenTB is an easy-to-use online tool to rapidly and accurately predict resistance to anti-tuberculosis drugs. GenTB can be accessed online at https://gentb.hms.harvard.edu, and the source code is available at https://github.com/farhat-lab/gentb-site.
%B Genome Medicine %G eng %U https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-021-00953-4 %0 Journal Article %J Antimicrobial Agents and Chemotherapy %D 2021 %T The role of epistasis in amikacin, kanamycin, bedaquiline, and clofazimine resistance in Mycobacterium tuberculosis complex %A Vargas R %A Freschi L %A Spitaleri A, %A Tahseen S %A Barilar I %A Neimann S, %A Miotto P %A Cirillo D %A Koser C, %A MR, Farhat %X
Antibiotic resistance among bacterial pathogens poses a major global health threat. M. tuberculosis complex (MTBC) is estimated to have the highest resistance rates of any pathogen globally. Given the slow growth rate and the need for a biosafety level 3 laboratory, the only realistic avenue to scale up drug susceptibility testing (DST) for this pathogen is to rely on genotypic techniques. This raises the fundamental question of whether a mutation is a reliable surrogate for phenotypic resistance or whether the presence of a second mutation can completely counteract its effect, resulting in major diagnostic errors (i.e. systematic false resistance results). To date, such epistatic interactions have only been reported for streptomycin that is now rarely used. By analyzing more than 31,000 MTBC genomes, we demonstrated that the eis C-14T promoter mutation, which is interrogated by several genotypic DST assays endorsed by the World Health Organization, cannot confer resistance to amikacin and kanamycin if it coincides with loss-of-function (LoF) mutations in the coding region of eis. To our knowledge, this represents the first definitive example of antibiotic reversion in MTBC. Moreover, we raise the possibility that mmpR (Rv0678) mutations are not valid markers of resistance to bedaquiline and clofazimine if these coincide with a LoF mutation in the efflux pump encoded by mmpS5 (Rv0677c) and mmpL5 (Rv0676c).
%B Antimicrobial Agents and Chemotherapy %G eng %U https://journals.asm.org/doi/10.1128/AAC.01164-21 %0 Journal Article %J JAMA Surgery %D 2021 %T Association Between NEDD4L Variation and the Genetic Risk of Acute Appendicitis, A Multi-institutional Genome-Wide Association Study. %A Kaafarani H %A Gaitanidis A %A Farhat MR. %A Christensen M, %A Breen K, %A Mendoza A, %A Fagenholz P, %A Velmahos G. %XImportance The familial aspect of acute appendicitis (AA) has been proposed, but its hereditary basis remains undetermined.
Objective To identify genomic variants associated with AA.
Design, Setting, and Participants This genome-wide association study, conducted from June 21, 2019, to February 4, 2020, used a multi-institutional biobank to retrospectively identify patients with AA across 8 single-nucleotide variation (SNV) genotyping batches. The study also examined differential gene expression in appendiceal tissue samples between patients with AA and controls using the GSE9579 data set in the National Institutes of Health’s Gene Expression Omnibus repository. Statistical analysis was conducted from October 1, 2019, to February 4, 2020.
Main Outcomes and Measures Single-nucleotide variations with a minor allele frequency of 5% or higher were tested for association with AA using a linear mixed model. The significance threshold was set at P = 5 × 10−8.
Results A total of 29 706 patients (15 088 women [50.8%]; mean [SD] age at enrollment, 60.1 [17.0] years) were included, 1743 of whom had a history of AA. The genomic inflation factor for the cohort was 1.003. A previously unknown SNV at chromosome 18q was found to be associated with AA (rs9953918: odds ratio, 0.99; 95% CI, 0.98-1.00; P = 4.48 × 10−8). This SNV is located in an intron of the NEDD4L gene. The heritability of appendicitis was estimated at 30.1%. Gene expression data from appendiceal tissue donors identified NEDD4L to be among the most differentially expressed genes (14 of 22 216 genes; β [SE] = −2.71 [0.44]; log fold change = −1.69; adjusted P = .04).
Conclusions and Relevance This study identified SNVs within the NEDD4L gene as being associated with AA. Nedd4l is involved in the ubiquitination of intestinal ion channels and decreased Nedd4l activity may be implicated in the pathogenesis of AA. These findings can improve the understanding of the genetic predisposition to and pathogenesis of AA.
%B JAMA Surgery %G eng %U https://jamanetwork.com/journals/jamasurgery/article-abstract/2782356 %0 Journal Article %J The Journal of Trauma and Acute Care Therapy %D 2021 %T Multisystem outcomes and predictors of mortality in critically ill patients with COVID-19: Demographics and disease acuity matter more than comorbidities or treatment modalities, Journal of Trauma and Acute Care Surgery %A Alser, O %A Mokhtari, A %A Naar, L %A Langeveld, K %A Breen, K %A Farhat, Maha R %B The Journal of Trauma and Acute Care Therapy %V 90 %P 880-890 %G eng %U https://journals.lww.com/jtrauma/Abstract/2021/05000/Multisystem_outcomes_and_predictors_of_mortality.14.aspx %N 5 %0 Journal Article %J bioRxiv %D 2021 %T Genomic sequence characteristics and the empiric accuracy of short-read sequencing %A Marin, M %A Vargas, R %A M. Harris %A Jeffrey, B %A Epperson, L.E %A Durbin, D %A Strong, M %A Salfinger, M %A Iqbal, Z %A Akhundova, I %A Vashakidze, S %A Crudu, V %A Rosenthal, A %A Farhat, M R %X Background: Short-read whole genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences, and sequencing bias, reduce the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. For the clonal pathogen Mycobacterium tuberculosis (Mtb), researchers frequently exclude 10.7% of the genome believed to be repetitive and prone to erroneous variant calls. To benchmark short-read variant calling, we used 36 diverse clinical Mtb isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically study the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias, and GC content. Results: Reference based Illumina variant calling had a recall ≥89.0% and precision ≥98.5% across parameters evaluated. The best balance between precision and recall was achieved by tuning the mapping quality (MQ) threshold, i.e. confidence of the read mapping (recall 85.8%, precision 99.1% at MQ ≥ 40). Masking repetitive sequence content is an alternative conservative approach to variant calling that maintains high precision (recall 70.2%, precision 99.6% at MQ≥40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52 of the 168 PE/PPE genes (34.5%). We present a refined list of low confidence regions and examine the largest sources of variant calling error. Conclusions: Our improved approach to variant calling has broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems, and more generally for WGS applications in other organisms. %B bioRxiv %G eng %U https://www.biorxiv.org/content/10.1101/2021.04.08.438862v1 %0 Journal Article %J Lancet Infectious Diseases %D 2021 %T Measuring healthcare delays among privately insured tuberculosis patients in the United States: an observational cohort study. %A El Halabi, J %A Palmer, N. P. %A Fox, K %A Golub, JE %A Kohane, I. %A Farhat, Maha R %B Lancet Infectious Diseases %G eng %U https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30732-5/fulltext %0 Journal Article %J The Lancet %D 2021 %T A Legacy of disease %A Groschel M, %A MR, Farhat %B The Lancet %V 21 %G eng %U https://doi.org/10.1016/S1473-3099(21)00165-1 %N 3 %0 Journal Article %J eLife %D 2021 %T In-host population dynamics of Mycobacterium tuberculosis complex during active disease %A Vargas R. %A Freschi L %A Marin M %A Epperson E %A Smith M %A Oussenko I %A Durbin D %A Strong M %A Salfinger M %A Farhat MR. %XTuberculosis (TB) is a leading cause of death globally. Understanding the population dynamics of TB’s causative agent Mycobacterium tuberculosis complex (Mtbc) in-host is vital for understanding the efficacy of antibiotic treatment. We use longitudinally collected clinical Mtbc isolates that underwent Whole-Genome Sequencing from the sputa of 200 patients to investigate Mtbc diversity during the course of active TB disease after excluding 107 cases suspected of reinfection, mixed infection or contamination. Of the 178/200 patients with persistent clonal infection >2 months, 27 developed new resistance mutations between sampling with 20/27 occurring in patients with pre-existing resistance. Low abundance resistance variants at a purity of ≥19% in the first isolate predict fixation in the subsequent sample. We identify significant in-host variation in 27 genes, including antibiotic resistance genes, metabolic genes and genes known to modulate host innate immunity and confirm several to be under positive selection by assessing phylogenetic convergence across a genetically diverse sample of 20,352 isolates.
%B eLife %G eng %U https://doi.org/10.7554/eLife.61805.sa2 %0 Journal Article %J The Lancet Microbe %D 2021 %T Globally diverse Mycobacterium tuberculosis resistance acquisition: a retrospective geographical and temporal analysis of whole genome sequences %A Ektefaie Y %A Dixit A %A Freschi L %A MR, Farhat %B The Lancet Microbe %V 2 %P e96 - e104 %G eng %U https://doi.org/10.1016/S2666-5247(20)30195-6 %N 3 %0 Magazine Article %D 2020 %T When our internship went virtual we needed a new approach %A Naomi Rankin %A Matthias Groshel %A Farhat, Maha %B Science Magazine %G eng %0 Journal Article %D 2020 %T Population structure, biogeography and transmissibility of Mycobacterium tuberculosis %A Freschi L %A Vargas Jr R %A Hussain A %A Kamal SMM %A Skrahina A %A Tahseen S %A Ismail N %A Barbova A %A Niemann S %A Cirillo DM %A Dean AS %A Zignol M %A MR, Farhat %X Mycobacterium tuberculosis is a clonal pathogen proposed to have co-evolved with its human host for millennia, yet our understanding of its genomic diversity and biogeography remains incomplete. Here we use a combination of phylogenetics and dimensionality reduction to reevaluate the population structure of M. tuberculosis, providing the first in-depth analysis of the ancient East African Indian Lineage 1 and the modern Central Asian Lineage 3 and expanding our understanding of Lineages 2 and 4. We assess sub-lineages using genomic sequences from 4,939 pan-susceptible strains and find 30 new genetically distinct clades that we validate in a dataset of 4,645 independent isolates. We characterize sub-lineage geographic distributions and demonstrate a consistent geographically restricted and unrestricted pattern for 20 groups, including three groups of Lineage 1. We assess the transmissibility of the four major lineages by examining the distribution of terminal branch lengths across the M. tuberculosis phylogeny and identify evidence supporting higher transmissibility in Lineages 2 and 4 than 3 and 1 on a global scale. We define a robust expanded barcode of 95 single nucleotide substitutions (SNS) that allows for the rapid identification of 69 Mtb sub-lineages and 26 additional internal groups. Our results paint a higher resolution picture of the Mtb phylogeny and biogeography. %G eng %U https://www.biorxiv.org/content/10.1101/2020.09.29.293274v1 %0 Journal Article %J JAMA %D 2020 %T Gastrointestinal Complications in Critically Ill Patients With and Without COVID-19 %A El Moheb M %A Naar L %A Christensen MA %A Kapoen C %A Mauer LR %A MR, Farhat %A Kaafarani HMA %X Coronavirus disease 2019 (COVID-19) appears to have significant extrapulmonary complications affecting multiple organ systems.1-3 Critically ill patients with COVID-19 often develop gastrointestinal complications during their hospital stay, including bowel ischemia, transaminitis, gastrointestinal bleeding, pancreatitis, Ogilvie syndrome, and severe ileus.3 Whether the high incidence of gastrointestinal complications is a manifestation of critical illness in general or is specific to COVID-19 remains unclear. We compared the incidence of gastrointestinal complications of critically ill patients with COVID-19–induced acute respiratory distress syndrome (ARDS) vs comparably ill patients with non–COVID-19 ARDS using propensity score analysis. %B JAMA %G eng %0 Journal Article %J The Lancet Infectious Diseases %D 2020 %T Measuring healthcare delays among privately insured tuberculosis patients in the United States: an observational cohort study. %A El Halabi J %A Palmer NP %A Fox L %A Goleb JE %A Kohane I %A MR, Farhat %B The Lancet Infectious Diseases %G eng %0 Journal Article %D 2020 %T Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events %A Lemieux J %A Siddle KJ %A Shaw BM %A Loreth C %A Schaffner S %A Gladden-Young A %A Adams G %A Fink T %A Tomkins-Tinch CH %A Krasilnikova LA %A Deruff KC %A Rudy M %A Bauer MR %A Lagerborg KA %A Normandin E %A Chapman SB %A Reilly SK %A Anahtar MN %A Lin AE %A Carter A %A Myhrvold C %A Kemball M %A Chaluvadi SR %A Cusick C %A Flowers K %A Neumann A %A Cerrato F %A MR, Farhat %A Slater D %A Harris JB %A Branda J %A Hooper D %A Gaeta JM %A Bagett TP %A O'Connel J %A Gnirke A %A Lieberman TB %A Philippakis A %A Burns M %A Brown C %A Luban J %A Ryan ET %A Turbett SE %A LaRocque RC %A Hanage WP %A Gallagher G %A Madoff LC %A Smole S %A Pierce VM %A Rosenburg ES %A Sabeti S %A Park DJ %A MacInnis BL %XBackground
Improved genetic understanding of Mycobacterium tuberculosis (MTB) resistance to novel and repurposed anti-tubercular agents can aid the development of rapid molecular diagnostics.
Methods
Adhering to PRISMA guidelines, in March 2018, we performed a systematic review of studies implicating mutations in resistance through sequencing and phenotyping before and/or after spontaneous resistance evolution, as well as allelic exchange experiments. We focused on the novel drugs bedaquiline, delamanid, pretomanid and the repurposed drugs clofazimine and linezolid. A database of 1373 diverse control MTB whole genomes, isolated from patients not exposed to these drugs, was used to further assess genotype–phenotype associations.
Results
Of 2112 papers, 54 met the inclusion criteria. These studies characterized 277 mutations in the genes atpE, mmpR, pepQ, Rv1979c, fgd1, fbiABC and ddn and their association with resistance to one or more of the five drugs. The most frequent mutations for bedaquiline, clofazimine, linezolid, delamanid and pretomanid resistance were atpE A63P, mmpR frameshifts at nucleotides 192–198, rplC C154R, ddn W88* and ddn S11*, respectively. Frameshifts in the mmpR homopolymer region nucleotides 192–198 were identified in 52/1373 (4%) of the control isolates without prior exposure to bedaquiline or clofazimine. Of isolates resistant to one or more of the five drugs, 59/519 (11%) lacked a mutation explaining phenotypic resistance.
Conclusions
This systematic review supports the use of molecular methods for linezolid resistance detection. Resistance mechanisms involving non-essential genes show a diversity of mutations that will challenge molecular diagnosis of bedaquiline and nitroimidazole resistance. Combined phenotypic and genotypic surveillance is needed for these drugs in the short term.
%B Journal of Antimicrobial Chemotherapy %G eng %0 Journal Article %J Genomics %D 2020 %T The Global Phylogenetic Landscape and Nosocomial Spread of the Multidrug-Resistant Opportunist Stenotrophomonas Maltophilia %A Gröschel MI %A Meehan CJ, %A Barilar I %A Diricks M %A Gonzaga A %A Steglich M %A Conchillo-Solé O %A Scherer IC %A Mamat U %A Luz CF %A Bruyne KD %A Utpatel C %A Yero D %A Gibert I %A Daura X %A Kampmeier S %A Rahman NA %A Kresken M %A Werf TS %A Alio I %A Streit WR %A Zhou K %A Schwartz T %A Rossen JWA %A MR, Farhat %A Schaible UE %A Nübel U %A Rupp J %A Steinmann J %A Niemann S %A Kohl TA %XRecent studies portend a rising global spread and adaptation of human- or healthcare-associated pathogens. Here, we analysed an international collection of the emerging, multidrug-resistant, opportunistic pathogen Stenotrophomonas maltophilia from 22 countries to infer population structure and clonality at a global level. We show that the S. maltophilia complex is divided into 23 monophyletic lineages, most of which harboured strains of all degrees of human virulence. Lineage Sm6 comprised the highest rate of human-associated strains, linked to key virulence and resistance genes. Transmission analysis identified potential outbreak events of genetically closely related strains isolated within days or weeks in the same hospitals.
One Sentence Summary The S. maltophilia complex comprises genetically diverse, globally distributed lineages with evidence for intra-hospital transmission.
%B Genomics %G eng %U https://www.biorxiv.org/content/10.1101/748954v2 %0 Journal Article %J Molecular Biology and Evolotion %D 2020 %T GenomegaMap within-species genome-wide dN/dS estimation from over 10,000 genomes %A Wilson DJ %A The CRyPTIC Consortium %X The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well-estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in M. tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species. %B Molecular Biology and Evolotion %G eng %U https://academic.oup.com/mbe/advance-article/doi/10.1093/molbev/msaa069/5804989 %0 Journal Article %J Journal of Trauma and Acute Care Surgery %D 2020 %T Identification of a new genetic variant associated with cholecystitis: a multicenter genome-wide association study %A Gaitanidis A %A Bonde A %A Mendosa A %A Sillesen MH %A El Hechi M %A Velmahos G %A Kaafarani H %A MR, Farhat %XStudy type
Prognostic and Epidemiological
Motivation
Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages.
Results
We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification and developed DeepAMR_cluster, a clustering variant based on DeepAMR, for learning clusters in latent space of the data. The results showed that DeepAMR outperformed baseline model and four machine learning models with mean AUROC from 94.4% to 98.7% for predicting resistance to four first-line drugs [i.e. isoniazid (INH), ethambutol (EMB), rifampicin (RIF), pyrazinamide (PZA)], multi-drug resistant TB (MDR-TB) and pan-susceptible TB (PANS-TB: MTB that is susceptible to all four first-line anti-TB drugs). In the case of INH, EMB, PZA and MDR-TB, DeepAMR achieved its best mean sensitivity of 94.3%, 91.5%, 87.3% and 96.3%, respectively. While in the case of RIF and PANS-TB, it generated 94.2% and 92.2% sensitivity, which were lower than baseline model by 0.7% and 1.9%, respectively. t-SNE visualization shows that DeepAMR_cluster captures lineage-related clusters in the latent space.
%B Bioinformatics %V 35 %P 3240–3249 %G eng %U https://doi.org/10.1093/bioinformatics/btz067 %N 18 %0 Journal Article %J Lancet Infectious Diseases %D 2019 %T Microbial Evolutionary Medicine - from theory to clinical practice %A Anderson SB %A Shapiro JB %A Vandenbroucke-Grauls C %A de Vos, MGJ %X Bacteria and other microbes play a crucial role in human health and disease. Medicine and clinical microbiology have traditionally attempted to identify the etiological agents that causes disease, and how to eliminate them. Yet this traditional paradigm is becoming inadequate for dealing with a changing disease landscape. Major challenges to human health are noncommunicable chronic diseases, often driven by altered immunity and inflammation, and persistent communicable infections whose agents harbor antibiotic resistance. It is increasingly recognized that microbe-microbe interactions, as well as human-microbe interactions are important. Here, we review the "Evolutionary Medicine" framework to study how microbial communities influence human health. This approach aims to predict and manipulate microbial influences on human health by integrating ecology, evolutionary biology, microbiology, bioinformatics and clinical expertise. We focus on the potential promise of evolutionary medicine to address three key challenges: 1) detecting microbial transmission; 2) predicting antimicrobial resistance; 3) understanding microbe-microbe and human-microbe interactions in health and disease, in the context of the microbiome. %B Lancet Infectious Diseases %V 19 %P PE273-E283 %G eng %U https://doi.org/10.1016/S1473-3099(19)30045-3 %N 8 %0 Journal Article %J EBioMedicine %D 2019 %T Deep Learning Predicts Tuberculosis Drug Resistance Status from Whole-Genome Sequencing Data %A Chen ML %A Doddi A %A Royer J %A Freschi L %A Schito M %A Ezewudo M %A Kohane IS %A Beam A %A MR, Farhat %X The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited scope of conventional phenotypic drug susceptibility but gaps remain for predicting phenotype accurately from genotypic data. Using targeted or whole genome sequencing and conventional drug resistance phenotyping data from 3,601 Mycobacterium tuberculosis strains, 1,228 of which were multidrug resistant, we implemented the first multitask deep learning framework to predict phenotypic drug resistance to 10 anti-tubercular drugs. The proposed wide and deep neural network (WDNN) acheived improved predicted performance compared to regularized logistic regression and random forest: the average sensitivities and specificities, respectively, were 92.7% and 92.7% for first-line drugs and 82.0% and 92.8% for second-line drugs during cross-validation. On an independent validation set, the multitask WDNN showed significant performance gains over baseline models, with average sensitivities and specificities, respectively, of 84.5% and 93.6% for first-line drugs and 64.0% and 95.7% for second-line drugs. In addition to being able to learn from samples that have only been partially phenotyped, our proposed multitask architecture shares information across different anti-tubercular drugs and genes to provide a more accurate phenotypic prediction. We use t-distributed Stochastic Neighbor Embedding (t-SNE) visualization and feature importance analyses to examine inter-drug similarities. Deep learning has a clear role in improving drug resistance predictive performance over traditional methods and holds promise in bringing sequencing technologies closer to the bedside. %B EBioMedicine %V 43 %P 356-369 %8 March 2018 %G eng %U https://www.sciencedirect.com/science/article/pii/S2352396419302506?via%3Dihub %0 Journal Article %J Scientific Reports %D 2019 %T Whole genome sequencing identifies bacterial factors affecting transmission of multidrug-resistant tuberculosis in a high-prevalence setting %A Dixit A %A Freschi L %A Vargas R %A Calderon R %A Sacchettini J %A Drobniewski F %A Galea JT %A Contreras C %A Yataco R %A Zhang Z %A Lecca L %A Kolokotronis SO %A Mathema B %A MR, Farhat %X Whole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based TB transmissibility study in Peru, we identified a large MIRU-VNTR Mtb cluster (148 isolates) with a range of resistance phenotypes, and studied host and bacterial factors contributing to its spread. WGS was performed on 61 of the 148 isolates. We compared transmission link inference using epidemiological or genomic data and estimated the dates of emergence of the cluster and antimicrobial drug resistance (DR) acquisition events by generating a time-calibrated phylogeny. Using a set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages. Four of the 61 isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95%HPD: 1945-1985). Isoniazid resistance arose once and rifampin resistance emerged subsequently at least three times. Emergence of other DR types occurred as recently as within the last year of sampling. We identified five cluster-defining SNPs potentially contributing to tranmissibility. In conclusion, clusters (as defined by MIRU-VNTR typing) may be circulating for decades in a high-burden setting. WGS allows for an enhanced understanding of transmission, drug resistance, and bacterial fitness factors. %B Scientific Reports %V 9 %G eng %U https://www.nature.com/articles/s41598-019-41967-8 %N 5602 %0 Journal Article %J Journal of Antimicrobial Chemotherapy %D 2019 %T Rifampicin and rifabutin resistance in 1000 Mycobacterium tuberculosis clinical isolates %A MR, Farhat %A Sixsmith J %A Calderon R %A Hicks N %A Fortune S %A M, Murray %XObjectives
Drug-resistant TB remains a public health challenge. Rifamycins are among the most potent anti-TB drugs. They are known to target the RpoB subunit of RNA polymerase; however, our understanding of how rifamycin resistance is genetically coded remains incomplete. Here we investigated rpoB genetic diversity and cross-resistance between the two rifamycin drugs rifampicin and rifabutin.
Methods
We performed WGS of 1003 Mycobacterium tuberculosis clinical isoltes and determined MICs of both rifamycin agents on 7H10 agar using the indirect proportion method. We generated rpoB mutants in a laboratory strain and measured their antibiotic susceptibility using the alamarBlue reduction assay.
Results
Of the 1003 isolates, 766 were rifampicin resistant and 210 (27%) of these were ribabutin susceptible; j102/210 isolates had the rpoB mutation D435V (Escherichia coli D516V). Isolates with discordant resistance were 17.2 times more likely to harbour a D435V mutation than those resistant to both agents (OR 17.2, 95% CI 10.5-27.9, P value <10−40). Compared with WT, the D435V in vitro mutant had an increased IC50 of both rifamycins; however, in both cases to a lesser degree than the S450L (E. coli S531L) mutation.
Conclusions
The observation that the rpoB D435V mutation produces an increase in the IC50 of both drugs contrasts with findings from previous smaller studies that suggested that isolates with the D435V mutation remain rifabutin susceptible despite being rifampicin resistant. Our finding thus suggests that the recommended critical testing concentration for rifabutin should be revised.
%B Journal of Antimicrobial Chemotherapy %8 Sept 2018 %G eng %U https://academic.oup.com/jac/advance-article-abstract/doi/10.1093/jac/dkz048/5359497?redirectedFrom=fulltext %0 Journal Article %J Nature Microbiology %D 2019 %T Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings %A Schubert B %A Maddamsetti R %A Nyman J %A MR, Farhat %A Marks DS %X Genome analysis should allow the discovery of interdependent loci that together cause antibiotic resistance. In practive, however, the vast number of possible epistatic interactions erodes statistical power. Here, we extend an approach that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled. This approach reduces the number of tests required for an epistatic genome-wide association study of antibiotic resistance and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 240 epistatic pairs that influence the minimum inhibitory concentrations of 5 different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in a second dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of associations occurred in unreported genes, such as murE. About half of the discovered epistasis involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC. Still, many combinations involved unreported loci and genes. While most variation in minimum inhibitory concentrations could be explained by identified loci, epistasis substantially increased explained phenotypic variance. Our work provides a systematic identification of epistasis affecting antibiotic resistance in N. gonorrhoeae and a generalizable approach for epistatic genome-wide association studies. %B Nature Microbiology %V 4 %P 328-338 %8 30 May 2018 %G eng %U https://www.nature.com/articles/s41564-018-0309-1 %0 Journal Article %J Nature Reviews Microbiology %D 2019 %T Whole genome sequencing of Mycobacterium tuberculosis: current standards and open issues %A Meehan CJ, %A Serrano G.G. %A Kohl T %A Verboven L %A Dippenaar A %A Ezewudo M %A MR, Farhat %A Guthrie J %A Laukens K %A Miotto P %A Ofori-Anyinam B %A Dreyer V %A Supply P %A Suresh A %A Utpatel C %A D van Soolingen %A Zhou Y %A Ashton P %A Brites D %A Cabibbe A %A de Jong B %A De Vos M %A Fabrizio M %A Gagneux S %A Gao Q %A Heupink T %A Liu Q %A Louiseau CM %A Rigouts L %A Rodwell T %A Tagliani E %A Walker T %A Warren R %A Zhao Y %A Zignol M %A Schito M %A Gardy JL %A Cirillo D %A Niemann S %A Comas I %A Van Rie A %B Nature Reviews Microbiology %G eng %0 Journal Article %J Nature Communications %D 2018 %T GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions %A MR, Farhat %A Freschi L %A Calderon R %A Ioerger T %A Snyder M %A Meehan Conor J %A de Jong B %A Rigouts L %A Sloutsky A %A Kaur D %A Sunyaev S %A van Soolingen D %A Shendure J %A Sacchettini J %A M, Murray %X Drug resistance is threatening attempts at tuberculosis epidemic control. Molecular diagnostics for drug resistance that rely on the detection of resistance-related mutations could expedite patient care and accelerate progress in TB eradication. We performed minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We then used a linear mixed model to evaluate genome wide associations between mutations in MTB genes or noncoding regions and drug resistance, followed by validation of our findings in an independent dataset of 792 patient isolates. Novel associations at 13 genomic loci were confirmed in the validation set, with 2 involving noncoding regions. We found promoter mutations to have smaller average effects on resistance levels than gene body mutations in genes where both can contribute to resistance. Enabled by a quantitative measure of resistance, we estimated the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. We also report the proportion of variation in resistance levels explained by the novel loci identified here. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causative or compensatory loci, and emphasizes the contribution of the noncoding portion of the genome. %B Nature Communications %8 2019 %G eng %U https://www.biorxiv.org/content/early/2018/09/27/429159 %0 Journal Article %J The New England Journal of Medicine %D 2018 %T Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing %A Walker TM %A Walker AS %A Peto TEA %A MR, Farhat %X
BACKGROUND
The World Health Organization recommends drug-susceptibility testing of Mycobacterium tuberculosis complex for all patients with tuberculosis to guide treatment decisions and improve outcomes. Whether DNA sequencing can be used to accurately predict profiles of susceptibility to first-line antituberculosis drugs has not been clear.
METHODS
We obtained whole-genome sequences and associated phenotypes of resistance or susceptibility to the first-line antituberculosis drugs isoniazid, rifampin, ethambutol, and pyrazinamide for isolates from 16 countries across six continents. For each isolate, mutations associated with drug resistance and drug susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These profiles were predicted to be susceptible to all four drugs (i.e., pansusceptible) if they were predicted to be susceptible to isoniazid and to the other drugs or if they contained mutations of unknown association in genes that affect susceptibility to the other drugs. We simulated the way in which the negative predictive value changed with the prevalence of drug resistance.
RESULTS
A total of 10,209 isolates were analyzed. The largest proportion of phenotypes was predicted for rifampin (9660 [95.4%] of 10,130) and the smallest was predicted for ethambutol (8794 [89.8%] of 9794). Resistance to isoniazid, rifampin, ethambutol, and pyrazinamide was correctly predicted with 97.1%, 97.5%, 94.6%, and 91.3% sensitivity, respectively, and susceptibility to these drugs was correctly predicted with 99.0%, 98.8%, 93.6%, and 96.8% specificity. Of the 7516 isolates with complete phenotypic drug-susceptibility profiles, 5865 (78.0%) had complete genotypic predictions, among which 5250 profiles (89.5%) were correctly predicted. Among the 4037 phenotypic profiles that were predicted to be pansusceptible, 3952 (97.9%) were correctly predicted.
CONCLUSIONS
Genotypic predictions of the susceptibility of M. tuberculosis to first-line drugs were found to be correlated with phenotypic susceptibility to these drugs. (Funded by the Bill and Melinda Gates Foundation and others.)
Background
Improving our understanding of the relationship between the genotype and the drug resistance phenotype of Mycobacterium tuberculosis will aid the development of more accurate molecular diagnostics for drug-resistant tuberculosis. Studies that use direct genetic manipulation to identify the mutations that cause M. tuberculosis drug resistance are superior to associational studies in elucidating an individual mutation's contribution to the drug resistance phenotype.
Methods
We systematically reviewed the literature for publications reporting allelic exchange experiements in any of the resistance-associated M. tuburculosis genes. We included studies that introduced single point mutations using specialized linkage transduction or site-directed/in vitro mutagenesis and documented a change in the resistance phenotype.
Results
We summarize evidence supporting the causal relationship of 54 different mutations in eight genes (katG, inhA, kasA, embB, rpoB, gyrA and gyrB) and one intergenic region (furA-katG) with resistance to isoniazid, the rifamycins, ethambutol and fluoroquinolones. We observed a significant role for the strain of genomic background in modulating the resistance phenotype of 21 of these mutations and found examples of where the same drug resistance mutations caused varying levels of resistance to different members of the same drug class.
Conclusions
This systematic review highlights those mutations that have been shown to causally change phenotypic resistance in M. tuberculosis and brings attention to a notable lack of allelic exchange data for several of the genes known to be associated with drug resistance.
%B J Antimicrob Chemother %V 69 %P 331-42 %G eng %U https://academic.oup.com/jac/article/69/2/331/712319 %N 2 %0 Journal Article %J Genome Med %D 2014 %T A phylogeny-based sampling strategy and power calculator informs genome-wide associations study design for microbial pathogens. %A MR, Farhat %A Shapiro BJ %A Sheppard SK %A Colijn C %A M, Murray %X Whole genome sequencing is increasingly used to study phenotypic variation among infectious pathogens and to evaluate their relative transmissibility, virulence, and immunogenicity. To date, relatively little has been published on how and how many pathogen strains should be selected for studies associating phenotype and genotype. There are specific challenges when identifying genetic associations in bacteria which often comprise highly structured populations. Here we consider general methodological questions related to sampling and analysis focusing on clonal to moderately recombining pathogens. We propose that a matched sampling scheme constitutes an efficient study design, and provide a power calculator based on phylogenetic convergence. We demonstrate this approach by applying it to genomic datasets for two microbial pathogens: Mycobacterium tuberculosis and Campylobacter species. %B Genome Med %V 6 %P 101 %8 2014 %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/25484920?dopt=Abstract %R 10.1186/s13073-014-0101-7 %0 Journal Article %J Eur Respir J %D 2013 %T Disturbance of respiratory muscle control in a patient with early-stage multiple sclerosis. %A MR, Farhat %A Loring SH %A Riskind P %A Weinhouse G %K Cyclophosphamide %K Disease Progression %K Dyspnea %K Electromyography %K Esophagus %K Female %K Humans %K Magnetic Resonance Imaging %K Manometry %K Middle Aged %K Multiple Sclerosis, Relapsing-Remitting %K Respiration Disorders %K Respiratory Function Tests %K Respiratory Muscles %B Eur Respir J %V 41 %P 1454-6 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23728406?dopt=Abstract %R 10.1183/09031936.00172312 %0 Journal Article %J Nat Genet %D 2013 %T Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis. %A MR, Farhat %A Shapiro BJ %A Kieser KJ %A Sultana R %A Jacobson KR %A Victor TC %A Warren RM %A Streicher EM %A Calver A %A Sloutsky A %A Kaur D %A Posey JE %A Plikaytis B %A Oggioni MR %A Gardy JL %A Johnston JC %A Rodrigues M %A Tang PKC %A Kato-Maeda M %A Borowsky ML %A Muddukrishna B %A Kreiswirth BN %A Kurepina N %A Galagan J %A Gagneux S %A Birren B %A Eric JR %A Lander ES %A Sabeti PC %A M, Murray %K DNA Repair %K Drug Resistance, Microbial %K Mutation %K Mycobacterium tuberculosis %K Selection, Genetic %X M. tuberculosis is evolving antibiotic resistance, threatening attempts at tuberculosis epidemic control. Mechanisms of resistance, including genetic changes favored by selection in resistant isolates, are incompletely understood. Using 116 newly sequenced and 7 previously sequenced M. tuberculosis whole genomes, we identified genome-wide signatures of positive selection specific to the 47 drug-resistant strains. By searching for convergent evolution--the independent fixation of mutations in the same nucleotide position or gene--we recovered 100% of a set of known resistance markers. We also found evidence of positive selection in an additional 39 genomic regions in resistant isolates. These regions encode components in cell wall biosynthesis, transcriptional regulation and DNA repair pathways. Mutations in these regions could directly confer resistance or compensate for fitness costs associated with resistance. Functional genetic analysis of mutations in one gene, ponA1, demonstrated an in vitro growth advantage in the presence of the drug rifampicin. %B Nat Genet %V 45 %P 1183-9 %8 2013 Oct %G eng %N 10 %1 http://www.ncbi.nlm.nih.gov/pubmed/23995135?dopt=Abstract %R 10.1038/ng.2747 %0 Book Section %B Respiratory care: Principles and Practice %D 2011 %T Chapter 47: Lung Cancer %A Farhat M %B Respiratory care: Principles and Practice %7 2nd %I Jones & Bartlett Learning %C Burlington, MA %P 971 %G eng %0 Journal Article %J Crit Care %D 2011 %T A comparison of early versus late initiation of renal replacement therapy in critically ill patients with acute kidney injury: a systematic review and meta-analysis. %A Karvellas CJ %A MR, Farhat %A Sajjad I %A Mogensen SS %A Leung AA %A Wald R %A Bagshaw SM %K Acute Kidney Injury %K Critical Care %K Humans %K Randomized Controlled Trials as Topic %K Renal Replacement Therapy %K Survival Analysis %K Time Factors %K Treatment Outcome %X INTRODUCTION: Our aim was to investigate the impact of early versus late initiation of renal replacement therapy (RRT) on clinical outcomes in critically ill patients with acute kidney injury (AKI). METHODS: Systematic review and meta-analysis were used in this study. PUBMED, EMBASE, SCOPUS, Web of Science and Cochrane Central Registry of Controlled Clinical Trials, and other sources were searched in July 2010. Eligible studies selected were cohort and randomised trials that assessed timing of initiation of RRT in critically ill adults with AKI. RESULTS: We identified 15 unique studies (2 randomised, 4 prospective cohort, 9 retrospective cohort) out of 1,494 citations. The overall methodological quality was low. Early, compared with late therapy, was associated with a significant improvement in 28-day mortality (odds ratio (OR) 0.45; 95% confidence interval (CI), 0.28 to 0.72). There was significant heterogeneity among the 15 pooled studies (I(2) = 78%). In subgroup analyses, stratifying by patient population (surgical, n = 8 vs. mixed, n = 7) or study design (prospective, n = 10 vs. retrospective, n = 5), there was no impact on the overall summary estimate for mortality. Meta-regression controlling for illness severity (Acute Physiology And Chronic Health Evaluation II (APACHE II)), baseline creatinine and urea did not impact the overall summary estimate for mortality. Of studies reporting secondary outcomes, five studies (out of seven) reported greater renal recovery, seven (out of eight) studies showed decreased duration of RRT and five (out of six) studies showed decreased ICU length of stay in the early, compared with late, RRT group. Early RRT did not; however, significantly affect the odds of dialysis dependence beyond hospitalization (OR 0.62 0.34 to 1.13, I(2) = 69.6%). CONCLUSIONS: Earlier institution of RRT in critically ill patients with AKI may have a beneficial impact on survival. However, this conclusion is based on heterogeneous studies of variable quality and only two randomised trials. In the absence of new evidence from suitably-designed randomised trials, a definitive treatment recommendation cannot be made. %B Crit Care %V 15 %P R72 %8 2011 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/21352532?dopt=Abstract %R 10.1186/cc10061 %0 Journal Article %J PLoS Comput Biol %D 2009 %T Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production. %A Colijn C %A Brandes A %A Zucker J %A Lun DS %A Weiner B %A MR, Farhat %A Cheng T-Y %A Moody DB %A M, Murray %A Galagan JE %K Algorithms %K Cluster Analysis %K Computational Biology %K Fatty Acids %K Gene Expression Profiling %K Gene Expression Regulation %K Gene Expression Regulation, Bacterial %K Genome, Bacterial %K Metabolic Networks and Pathways %K Models, Biological %K Models, Statistical %K Mycobacterium tuberculosis %K Mycolic Acids %K Reproducibility of Results %K Software %X Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression), extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB). Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data. %B PLoS Comput Biol %V 5 %P e1000489 %8 2009 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/19714220?dopt=Abstract %R 10.1371/journal.pcbi.1000489 %0 Journal Article %J Int J Tuberc Lung Dis %D 2008 %T Thinking in three dimensions: a web-based algorithm to aid the interpretation of tuberculin skin test results. %A Menzies, D %A Gardiner, G %A Farhat, M %A Greenaway, C %A Pai, M %K Adult %K Algorithms %K BCG Vaccine %K Decision Support Techniques %K Humans %K Internet %K Predictive Value of Tests %K Risk Assessment %K Software %K Tuberculin Test %K Tuberculosis %X BACKGROUND: The tuberculin skin test (TST) is the most widely used test for detecting tuberculosis (TB) infection. Accurate interpretation of TST requires consideration of three dimensions-the size of the skin reaction, the positive predictive value (PPV) and risk of disease. METHODS: We developed a web-based algorithm incorporating epidemiological, medical and radiographic risk factors to help in the interpretation of positive TST results in adults (http://www.meakins.mcgill.ca/meakins/NEW TST Calculator/homeE.htm). We used summary estimates from published reviews on the prevalence of latent TB infection, the likelihood of false-positive TST and risk of active TB disease. RESULTS: The algorithm calculations show that the most important determinants of risk of active disease are the presence of medical and radiographic risk factors, while the size of the reaction is of modest importance. In persons who have received bacille Calmette-Guérin vaccination after infancy, the algorithm calculations show that the PPV will be low. In such persons, the risk of disease is predicted to be very low, unless there are medical or radiographic risk factors that increase the risk of reactivation. CONCLUSIONS: Our web-based algorithm can generate clinically useful estimates of the annual and cumulative lifetime risk of developing TB in adults with a positive TST. %B Int J Tuberc Lung Dis %V 12 %P 498-505 %8 2008 May %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/18419884?dopt=Abstract %0 Journal Article %J N Engl J Med %D 2007 %T Case records of the Massachusetts General Hospital. Case 7-2007. A 59-year-old woman with diabetic renal disease and nonhealing skin ulcers. %A Bazari H %A Jaff MR %A Mannstadt M %A Yan S %K Aged %K Atherosclerosis %K Calciphylaxis %K Diabetes Mellitus, Type 2 %K Diabetic Foot %K Diabetic Nephropathies %K Diagnosis, Differential %K Female %K Humans %K Ischemia %K Leg %K Leg Ulcer %K Middle Aged %K Obesity, Morbid %K Osteomyelitis %K Pressure Ulcer %K Renal Insufficiency, Chronic %B N Engl J Med %V 356 %P 1049-57 %8 2007 Mar 8 %G eng %N 10 %1 http://www.ncbi.nlm.nih.gov/pubmed/17347459?dopt=Abstract %R 10.1056/NEJMcpc069038 %0 Journal Article %J Int J Tuberc Lung Dis %D 2007 %T False-positive tuberculin reactions due to non-tuberculous mycobacterial infections. %A Cobelens, FGJ %A Menzies, D %A Farhat, M R %K Adjuvants, Immunologic %K BCG Vaccine %K Humans %K Mycobacterium Infections, Nontuberculous %K Nontuberculous Mycobacteria %K Tuberculin Test %K Tuberculosis %B Int J Tuberc Lung Dis %V 11 %P 934-5;author reply 935 %8 2007 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/17705966?dopt=Abstract %0 Journal Article %J Int J Tuberc Lung Disease %D 2006 %T False-positive tuberculin reactions due to non-tuberculous mycobacterial infections %A Farhat M %A Greenaway C %A Pai M %A Menzies D %XDespite certain drawbacks, the tuberculin skin test (TST) remains in widespread use. Important advantages of the TST are its low cost, simplicity and interpretation based on extensive published literature. However, TST specificity is reduced by bacille Calmette-Guérin (BCG) vaccination and exposure to non-tuberculous mycobacteria (NTM).
To estimate TST specificity, we reviewed the published literature since 1966 regarding the effect of BCG vaccination and NTM infection on TST. Studies selected included healthy subjects with documented BCG vaccination status, including age at vaccination. Studies of NTM effect had used standardised NTM antigens in healthy subjects.
In 24 studies involving 240,203 subjects BCG-vaccinated as infants, 20,406 (8.5%) had a TST of 10+ mm attributable to BCG, but only 56/5639 (1%) were TST-positive if tested > or =10 years after BCG. In 12 studies of 12,728 subjects vaccinated after their first birthday, 5314 (41.8%) had a false-positive TST of 10+ mm, and 191/898 (21.2%) after 10 years. Type of tuberculin test did not modify these results. In 18 studies involving 1,169,105 subjects, the absolute prevalence of false-positive TST from NTM cross-reactivity ranged from 0.1% to 2.3% in different regions.
The effect on TST of BCG received in infancy is minimal, especially > or =10 years after vaccination. BCG received after infancy produces more frequent, more persistent and larger TST reactions. NTM is not a clinically important cause of false-positive TST, except in populations with a high prevalence of NTM sensitisation and a very low prevalence of TB infection.
%B Int J Tuberc Lung Disease %V 10 %P 1192-1204 %G eng %U https://www-ncbi-nlm-nih-gov.ezp-prod1.hul.harvard.edu/pubmed/?term=17131776 %N 11