Viral Dynamics of Omicron and Delta Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants With Implications for Timing of Release from Isolation: A Longitudinal Cohort Study.

BACKGROUND: In January 2022, US guidelines shifted to recommend isolation for 5 days from symptom onset, followed by 5 days of mask-wearing. However, viral dynamics and variant and vaccination impact on culture conversion are largely unknown. METHODS: We conducted a longitudinal study on a university campus, collecting daily anterior nasal swabs for at least 10 days for reverse-transcription polymerase chain reaction (RT-PCR) testing and culture, with antigen rapid diagnostic testing (RDT) on a subset. We compared culture positivity beyond day 5, time to culture conversion, and cycle threshold trend when calculated from diagnostic test, from symptom onset, by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, and by vaccination status. We evaluated sensitivity and specificity of RDT on days 4-6 compared with culture. RESULTS: Among 92 SARS-CoV-2 RT-PCR-positive participants, all completed the initial vaccine series; 17 (18.5%) were infected with Delta and 75 (81.5%) with Omicron. Seventeen percent of participants had positive cultures beyond day 5 from symptom onset, with the latest on day 12. There was no difference in time to culture conversion by variant or vaccination status. For 14 substudy participants, sensitivity and specificity of day 4-6 RDT were 100% and 86%, respectively. CONCLUSIONS: The majority of our Delta- and Omicron-infected cohort culture-converted by day 6, with no further impact of booster vaccination on sterilization or cycle threshold decay. We found that rapid antigen testing may provide reassurance of lack of infectiousness, though guidance to mask for days 6-10 is supported by our finding that 17% of participants remained culture-positive after isolation.

Early Introduction and Rise of the Omicron Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variant in Highly Vaccinated University Populations.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible in vaccinated and unvaccinated populations. The dynamics that govern its establishment and propensity toward fixation (reaching 100% frequency in the SARS-CoV-2 population) in communities remain unknown. Here, we describe the dynamics of Omicron at 3 institutions of higher education (IHEs) in the greater Boston area. METHODS: We use diagnostic and variant-specifying molecular assays and epidemiological analytical approaches to describe the rapid dominance of Omicron following its introduction into 3 IHEs with asymptomatic surveillance programs. RESULTS: We show that the establishment of Omicron at IHEs precedes that of the state and region and that the time to fixation is shorter at IHEs (9.5-12.5 days) than in the state (14.8 days) or region. We show that the trajectory of Omicron fixation among university employees resembles that of students, with a 2- to 3-day delay. Finally, we compare cycle threshold values in Omicron vs Delta variant cases on college campuses and identify lower viral loads among college affiliates who harbor Omicron infections. CONCLUSIONS: We document the rapid takeover of the Omicron variant at IHEs, reaching near-fixation within the span of 9.5-12.5 days despite lower viral loads, on average, than the previously dominant Delta variant. These findings highlight the transmissibility of Omicron, its propensity to rapidly dominate small populations, and the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.

Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias.

BACKGROUND: Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited. METHODS: We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes. RESULTS: Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread. CONCLUSIONS: We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

Projected Long-Term Impact of the Coronavirus Disease 2019 (COVID-19) Pandemic on Hepatitis C Outcomes in the United States: A Modeling Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic disrupted access to and uptake of hepatitis C virus (HCV) care services in the United States. It is unknown how substantially the pandemic will impact long-term HCV-related outcomes. METHODS: We used a microsimulation to estimate the 10-year impact of COVID-19 disruptions in healthcare delivery on HCV outcomes including identified infections, linkage to care, treatment initiation and completion, cirrhosis, and liver-related death. We modeled hypothetical scenarios consisting of an 18-month pandemic-related disruption in HCV care starting in March 2020 followed by varying returns to pre-pandemic rates of screening, linkage, and treatment through March 2030 and compared them to a counterfactual scenario in which there was no COVID-19 pandemic or disruptions in care. We also performed alternate scenario analyses in which the pandemic disruption lasted for 12 and 24 months. RESULTS: Compared to the "no pandemic" scenario, in the scenario in which there is no return to pre-pandemic levels of HCV care delivery, we estimate 1060 fewer identified cases, 21 additional cases of cirrhosis, and 16 additional liver-related deaths per 100 000 people. Only 3% of identified cases initiate treatment and <1% achieve sustained virologic response (SVR). Compared to "no pandemic," the best-case scenario in which an 18-month care disruption is followed by a return to pre-pandemic levels, we estimated a smaller proportion of infections identified and achieving SVR. CONCLUSIONS: A recommitment to the HCV epidemic in the United States that involves additional resources coupled with aggressive efforts to screen, link, and treat people with HCV is needed to overcome the COVID-19-related disruptions.

Methods for handling missing data in serially sampled sputum specimens for mycobacterial culture conversion calculation.

BACKGROUND: The occurrence and timing of mycobacterial culture conversion is used as a proxy for tuberculosis treatment response. When researchers serially sample sputum during tuberculosis studies, contamination or missed visits leads to missing data points. Traditionally, this is managed by ignoring missing data or simple carry-forward techniques. Statistically advanced multiple imputation methods potentially decrease bias and retain sample size and statistical power. METHODS: We analyzed data from 261 participants who provided weekly sputa for the first 12 weeks of tuberculosis treatment. We compared methods for handling missing data points in a longitudinal study with a time-to-event outcome. Our primary outcome was time to culture conversion, defined as two consecutive weeks with no Mycobacterium tuberculosis growth. Methods used to address missing data included: 1) available case analysis, 2) last observation carried forward, and 3) multiple imputation by fully conditional specification. For each method, we calculated the proportion culture converted and used survival analysis to estimate Kaplan-Meier curves, hazard ratios, and restricted mean survival times. We compared methods based on point estimates, confidence intervals, and conclusions to specific research questions. RESULTS: The three missing data methods lead to differences in the number of participants achieving conversion; 78 (32.8%) participants converted with available case analysis, 154 (64.7%) converted with last observation carried forward, and 184 (77.1%) converted with multiple imputation. Multiple imputation resulted in smaller point estimates than simple approaches with narrower confidence intervals. The adjusted hazard ratio for smear negative participants was 3.4 (95% CI 2.3, 5.1) using multiple imputation compared to 5.2 (95% CI 3.1, 8.7) using last observation carried forward and 5.0 (95% CI 2.4, 10.6) using available case analysis. CONCLUSION: We showed that accounting for missing sputum data through multiple imputation, a statistically valid approach under certain conditions, can lead to different conclusions than naïve methods. Careful consideration for how to handle missing data must be taken and be pre-specified prior to analysis. We used data from a TB study to demonstrate these concepts, however, the methods we described are broadly applicable to longitudinal missing data. We provide valuable statistical guidance and code for researchers to appropriately handle missing data in longitudinal studies.

Pandemic Response Requires Research Samples: A U.S. Safety-Net Hospital's Experience and Call for National Action.

Biorepositories provide a critical resource for gaining knowledge of emerging infectious diseases and offer a mechanism to rapidly respond to outbreaks; the emergence of the novel coronavirus, SARS-CoV-2, has proved their importance. During the COVID-19 pandemic, the absence of centralized, national biorepository efforts meant that the onus fell on individual institutions to establish sample repositories. As a safety-net hospital, Boston Medical Center (BMC) recognized the importance of creating a COVID-19 biorepository to both support critical science at BMC and ensure representation in research for its urban patient population, most of whom are from underserved communities. This article offers a realistic overview of the authors' experience in establishing this biorepository at the onset of the COVID-19 pandemic during the height of the first surge of cases in Boston, Massachusetts, with the hope that the challenges and solutions described are useful to other institutions. Going forward, funders, policymakers, and infectious disease and public health communities must support biorepository implementation as an essential element of future pandemic preparedness.

Decentralized Care for Rifampin-Resistant Tuberculosis, Western Cape, South Africa.

In 2011, South Africa implemented a policy to decentralize treatment for rifampin-resistant tuberculosis (TB) to reduce durations of hospitalization and enable local treatment. We assessed policy implementation in Western Cape Province, where services expanded from 6 specialized TB hospitals to 406 facilities, by analyzing National Health Laboratory Service data on TB during 2012-2015. We calculated the percentage of patients who visited a TB hospital <1 year after rifampin-resistant TB diagnosis, the median duration of their hospitalizations, and the total distance between facilities visited. We assessed temporal changes with linear regression and stratified results by location. Of 2,878 patients, 65% were from Cape Town. In Cape Town, 29% visited a TB hospital; elsewhere, 68% visited a TB hospital. We found that hospitalizations and travel distances were shorter in Cape Town than in the surrounding areas.

Enhanced Human Immunodeficiency Virus-1 Replication in CD4+ T Cells Derived From Individuals With Latent Mycobacterium tuberculosis Infection.

BACKGROUND: Mycobacterium tuberculosis (Mtb) and human immunodeficiency virus (HIV) coinfection increases mortality, accelerates progression to acquired immune deficiency syndrome, and exacerbates tuberculosis disease. However, the impact of pre-existing Mtb infection on subsequent HIV infection has not been fully explored. We hypothesized that Mtb infection creates an immunological environment that influences the course of HIV infection, and we investigated whether pre-existing Mtb infection impacts the susceptibility of CD4+ T cells to HIV-1 infection. METHODS: Plasma and blood CD4+ T cells isolated from HIV-negative individuals across the Mtb infection spectrum and non-Mtb-infected control individuals were analyzed for inflammation markers and T-cell phenotypes. CD4+ T cells were infected with HIV-1 in vitro and were monitored for viral replication. RESULTS: We observed differences in proinflammatory cytokines and the relative proportion of memory T-cell subsets depending on Mtb infection status. CD4+ T cells derived from individuals with latent Mtb infection supported more efficient HIV-1 transcription, release, and replication. Enhanced HIV-1 replication correlated with higher percentages of CD4+ TEM and TTD cells. CONCLUSIONS: Pre-existing Mtb infection creates an immunological environment that reflects Mtb infection status and influences the susceptibility of CD4+ T cells to HIV-1 replication. These findings provide cellular and molecular insights into how pre-existing Mtb infection influences HIV-1 pathogenesis.

Prevalence, Predictors, and Successful Treatment Outcomes of Xpert MTB/RIF-identified Rifampicin-resistant Tuberculosis in Post-conflict Eastern Democratic Republic of the Congo, 2012-2017: A Retrospective Province-Wide Cohort Study.

BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) jeopardizes global TB control. The prevalence and predictors of Rifampicin-resistant (RR) TB, a proxy for MDR-TB, and the treatment outcomes with standard and shortened regimens have not been assessed in post-conflict regions, such as the South Kivu province in the eastern Democratic Republic of the Congo (DRC). We aimed to fill this knowledge gap and to inform the DRC National TB Program. METHODS: of adults and children evaluated for pulmonary TB by sputum smear microscopy and Xpert MTB/RIF (Xpert) from February 2012 to June 2017. Multivariable logistic regression, Kaplan-Meier estimates, and multivariable Cox regression were used to assess independent predictors of RR-TB and treatment failure/death. RESULTS: Of 1535 patients Xpert-positive for TB, 11% had RR-TB. Independent predictors of RR-TB were a positive sputum smear (adjusted odds ratio [aOR] 2.42, 95% confidence interval [CI] 1.63-3.59), retreatment of TB (aOR 4.92, 95% CI 2.31-10.45), and one or more prior TB episodes (aOR 1.77 per episode, 95% CI 1.01-3.10). Over 45% of RR-TB patients had no prior TB history or treatment. The median time from Xpert diagnosis to RR-TB treatment initiation was 12 days (interquartile range 3-60.2). Cures were achieved in 30/36 (83%) and 84/114 (74%) of patients on 9- vs 20/24-month MDR-TB regimens, respectively (P = .06). Predictors of treatment failure/death were the absence of directly observed therapy (DOT; adjusted hazard ratio [aHR] 2.77, 95% CI 1.2-6.66) and any serious adverse drug event (aHR 4.28, 95% CI 1.88-9.71). CONCLUSIONS: Favorable RR-TB cure rates are achievable in this post-conflict setting with a high RR-TB prevalence. An expanded Xpert scale-up; the prompt initiation of shorter, safer, highly effective MDR-TB regimens; and treatment adherence support are critically needed to optimize outcomes.

Using routinely collected laboratory data to identify high rifampicin-resistant tuberculosis burden communities in the Western Cape Province, South Africa: A retrospective spatiotemporal analysis.

BACKGROUND: South Africa has the highest tuberculosis incidence globally (781/100,000), with an estimated 4.3% of cases being rifampicin resistant (RR). Control and elimination strategies will require detailed spatial information to understand where drug-resistant tuberculosis exists and why it persists in those communities. We demonstrate a method to enable drug-resistant tuberculosis monitoring by identifying high-burden communities in the Western Cape Province using routinely collected laboratory data. METHODS AND FINDINGS: We retrospectively identified cases of microbiologically confirmed tuberculosis and RR-tuberculosis from all biological samples submitted for tuberculosis testing (n = 2,219,891) to the Western Cape National Health Laboratory Services (NHLS) between January 1, 2008, and June 30, 2013. Because the NHLS database lacks unique patient identifiers, we performed a series of record-linking processes to match specimen records to individual patients. We counted an individual as having a single disease episode if their positive samples came from within two years of each other. Cases were aggregated by clinic location (n = 302) to estimate the percentage of tuberculosis cases with rifampicin resistance per clinic. We used inverse distance weighting (IDW) to produce heatmaps of the RR-tuberculosis percentage across the province. Regression was used to estimate annual changes in the RR-tuberculosis percentage by clinic, and estimated average size and direction of change was mapped. We identified 799,779 individuals who had specimens submitted from mappable clinics for testing, of whom 222,735 (27.8%) had microbiologically confirmed tuberculosis. The study population was 43% female, the median age was 36 years (IQR 27-44), and 10,255 (4.6%, 95% CI: 4.6-4.7) cases had documented rifampicin resistance. Among individuals with microbiologically confirmed tuberculosis, 8,947 (4.0%) had more than one disease episode during the study period. The percentage of tuberculosis cases with rifampicin resistance documented among these individuals was 11.4% (95% CI: 10.7-12.0). Overall, the percentage of tuberculosis cases that were RR-tuberculosis was spatially heterogeneous, ranging from 0% to 25% across the province. Our maps reveal significant yearly fluctuations in RR-tuberculosis percentages at several locations. Additionally, the directions of change over time in RR-tuberculosis percentage were not uniform. The main limitation of this study is the lack of unique patient identifiers in the NHLS database, rendering findings to be estimates reliant on the accuracy of the person-matching algorithm. CONCLUSIONS: Our maps reveal striking spatial and temporal heterogeneity in RR-tuberculosis percentages across this province. We demonstrate the potential to monitor RR-tuberculosis spatially and temporally with routinely collected laboratory data, enabling improved resource targeting and more rapid locally appropriate interventions.

Impact of alcohol consumption on tuberculosis treatment outcomes: a prospective longitudinal cohort study protocol.

BACKGROUND: An estimated 10% of tuberculosis (TB) deaths are attributable to problematic alcohol use globally, however the causal pathways through which problem alcohol use has an impact on TB treatment outcome is not clear. This study aims to improve understanding of these mechanisms. Specifically, we aim to 1) assess whether poor TB treatment outcomes, measured as delayed time-to-culture conversion, are associated with problem alcohol use after controlling for non-adherence to TB pharmacotherapy; and 2) to determine whether pharmacokinetic (PK) changes in those with problem alcohol use are associated with delayed culture conversion, higher treatment failure/relapse rates or with increased toxicity. METHODS: Our longitudinal, repeated measures, prospective cohort study aims to examine the associations between problem alcohol use and TB treatment outcomes and to evaluate the effect of alcohol on the PK and pharmacodynamics (PD) of TB drugs. We will recruit 438 microbiologically confirmed, pulmonary TB patients with evidence of rifampicin susceptibility in Worcester, South Africa with 200 HIV uninfected patients co-enrolled in the PK aim. Participants are followed for the six months of TB treatment and an additional 12 months thereafter, with sputum collected weekly for the first 12 weeks of treatment, alcohol consumption measures repeated monthly in concert with an alcohol biomarker (phosphatidylethanol) measurement at baseline, and in person directly observed therapy (DOT) using real-time mobile phone-based adherence monitoring. The primary outcome is based on time to culture conversion with the second objective to compare PK of first line TB therapy in those with and without problem alcohol use. DISCUSSION: Globally, an urgent need exists to identify modifiable drivers of poor TB treatment outcomes. There is a critical need for more effective TB treatment strategies for patients with a history of problem alcohol use. However, it is not known whether poor treatment outcomes in alcohol using patients are solely attributable to noncompliance. This study will attempt to answer this question and provide guidance for future TB intervention trials. TRIAL REGISTRATION: Clinicaltrials.gov Registration Number: NCT02840877 . Registered on 19 July 2016.

Tuberculosis.

This issue provides a clinical overview of tuberculosis, focusing on screening, prevention, diagnosis, and treatment. The content of In the Clinic is drawn from the clinical information and education resources of the American College of Physicians (ACP), including MKSAP (Medical Knowledge and Self-Assessment Program). Annals of Internal Medicine editors develop In the Clinic in collaboration with the ACP's Medical Education and Publishing divisions and with the assistance of additional science writers and physician writers.

Fluoroquinolone Resistance Mutation Detection Is Equivalent to Culture-Based Drug Sensitivity Testing for Predicting Multidrug-Resistant Tuberculosis Treatment Outcome: A Retrospective Cohort Study.

BACKGROUND: Molecular diagnostics that rapidly and accurately predict fluoroquinolone (FQ) resistance promise to improve treatment outcomes for individuals with multidrug-resistant (MDR) tuberculosis (TB). Mutations in the gyr genes, though, can cause variable levels of in vitro FQ resistance, and some in vitro resistance remains unexplained by gyr mutations alone, but the implications of these discrepancies for treatment outcome are unknown. METHODS: We performed a retrospective cohort study of 172 subjects with MDR/extensively drug-resistant TB subjects and sequenced the full gyrA and gyrB open reading frames in their respective sputum TB isolates. The gyr mutations were classified into 2 categories: a set of mutations that encode high-level FQ resistance and a second set that encodes intermediate resistance levels. We constructed a Cox proportional model to assess the effect of the gyr mutation type on the time to death or treatment failure and compared this with in vitro FQ resistance, controlling for host and treatment factors. RESULTS: Controlling for other host and treatment factors and compared with patients with isolates without gyr resistance mutations, "high-level" gyr mutations significantly predict poor treatment outcomes with a hazard ratio of 2.6 (1.2-5.6). We observed a hazard of death and treatment failure with "intermediate-level" gyr mutations of 1.3 (0.6-3.1), which did not reach statistical significance. The gyr mutations were not different than culture-based FQ drug susceptibility testing in predicting the hazard of death or treatment failure and may be superior. CONCLUSIONS: FQ molecular-based diagnostic tests may better predict treatment response than traditional drug susceptibility testing and open avenues for personalizing TB therapy.

Implications of Failure to Routinely Diagnose Resistance to Second-Line Drugs in Patients With Rifampicin-Resistant Tuberculosis on Xpert MTB/RIF: A Multisite Observational Study.

BACKGROUND.: Xpert MTB/RIF (Xpert) detects rifampicin-resistant tuberculosis (RR-tuberculosis), enabling physicians to rapidly initiate a World Health Organization-recommended 5-drug regimen while awaiting second-line drug-susceptibility test (DST) results. We quantified the second-line DST results time and proportion of patients potentially placed on suboptimal therapy. METHODS.: We included RR-tuberculosis patients detected using Xpert at the South African National Health Laboratory Services (NHLS) of the Western Cape between November 2011 and June 2013 and at Eastern Cape, Free State, and Gauteng NHLS between November 2012 and December 2013. We calculated time from specimen collection to phenotypic second-line DST results. We identified isoniazid and ethionamide resistance mutations on line probe assay and performed pyrazinamide sequencing. RESULTS.: Among 1332 RR-tuberculosis patients, only 44.7% (596) had second-line DST for both fluoroquinolones and second-line injectable: 55.8% (466 of 835) in the Western Cape and 26.2% (130 of 497) in the other provinces. Patients with smear negative disease and age ≤10 years were less likely to have a result (risk ratio [RR] = 0.72; 95% CI, 0.64-0.81 and RR = 0.49; 95% CI, 0.26-0.79). Median time to second-line DST was 53 days (range, 8-259). Of the 252 patients with complete second-line DST, 101 (40.1%) potentially initiated a suboptimal regimen: 46.8% in the Western Cape and 25.3% in the other provinces. CONCLUSIONS.: Many South Africans diagnosed with RR-tuberculosis by Xpert initiate a suboptimal regimen, with information to adjust therapy available in half of all patients after a median 7 weeks. Algorithm completion and time delays remain challenging.

Gyrase Mutations Are Associated with Variable Levels of Fluoroquinolone Resistance in Mycobacterium tuberculosis.

Molecular diagnostics that rapidly and accurately predict resistance to fluoroquinolone drugs and especially later-generation agents promise to improve treatment outcomes for patients with multidrug-resistant tuberculosis and prevent the spread of disease. Mutations in the gyr genes are known to confer most fluoroquinolone resistance, but knowledge about the effects of gyr mutations on susceptibility to early- versus later-generation fluoroquinolones and about the role of mutation-mutation interactions is limited. Here, we sequenced the full gyrA and gyrB open reading frames in 240 multidrug-resistant and extensively drug-resistant tuberculosis strains and quantified their ofloxacin and moxifloxacin MIC by testing growth at six concentrations for each drug. We constructed a multivariate regression model to assess both the individual mutation effects and interactions on the drug MICs. We found that gyrB mutations contribute to fluoroquinolone resistance both individually and through interactions with gyrA mutations. These effects were statistically significant. In these clinical isolates, several gyrA and gyrB mutations conferred different levels of resistance to ofloxacin and moxifloxacin. Consideration of gyr mutation combinations during the interpretation of molecular test results may improve the accuracy of predicting the fluoroquinolone resistance phenotype. Further, the differential effects of gyr mutations on the activity of early- and later-generation fluoroquinolones requires further investigation and could inform the selection of a fluoroquinolone for treatment.

Systematic review of allelic exchange experiments aimed at identifying mutations that confer drug resistance in Mycobacterium tuberculosis.

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 experiments in any of the resistance-associated M. tuberculosis 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, embC, 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 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.

Analysis of the limited M. tuberculosis accessory genome reveals potential pitfalls of pan-genome analysis approaches.

Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.