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The pH sensor exploits the phenomenon of upconversion luminescence and is based on a hydrogel matrix containing (a) nanorods of the NaYF4:Er,Yb type that can be excited with 980-nm laser light to give a green and red (dual) emission, and (b) a longwave absorbing pH probe that causes a pH-dependent inner filter effect. [ABSTRACT FROM AUTHOR]

The pH sensor exploits the phenomenon of upconversion luminescence and is based on a hydrogel matrix containing (a) nanorods of the NaYF4:Er,Yb type that can be excited with 980-nm laser light to give a green and red (dual) emission, and (b) a longwave absorbing pH probe that causes a pH-dependent inner filter effect. [ABSTRACT FROM AUTHOR]

HIV targets CD4 T cells, which are required for the induction of high-affinity antibody responses and the formation of long-lived B cell memory. The depletion of antigen-specific CD4 T cells during HIV infection is therefore believed to impede the development of protective B cell immunity. Although several different HIVrelated B cell dysfunctions have been described, the role of CD4 T follicular helper (TFH) cells in HIV infection remains unknown. Here, we assessed HIV-specific TFH responses in the lymph nodes of treatment-naive and antiretroviral-treated HIV-infected individuals. Strikingly, both the bulk TFH and HIV-specific TFH cell populations were significantly expanded in chronic HIV infection and were highly associated with viremia. In particular, GAG-specific TFH cells were detected at significantly higher levels in the lymph nodes compared with those of GP120-specific TFH cells and showed preferential secretion of the helper cytokine IL-21. In addition, TFH cell expansion was associated with an increase of germinal center B cells and plasma cells as well as IgG1 hypersecretion. Thus, our study suggests that high levels of HIV viremia drive the expansion of TFH cells, which in turn leads to perturbations of B cell differentiation, resulting in dysregulated antibody production. [ABSTRACT FROM AUTHOR]

Functional defects in cytotoxic CD8+ T cell responses arise in chronic human viral infections, but the mechanisms involved are not well understood. In mice, CD4 cell-mediated interleukin-21 (IL-21) production is necessary for the maintenance of CD8+ T cell function and control of persistent viral infections. To investigate the potential role of IL-21 in a chronic human viral infection, we studied the rare subset of HIV-1 controllers, who are able to spontaneously control HIV-1 replication without treatment. HIV-specific triggering of IL-21 by CD4+ T cells was significantly enriched in these persons (P = 0.0007), while isolated loss of IL-21-secreting CD4+ T cells was characteristic for subjects with persistent viremia and progressive disease. IL-21 responses were mediated by recognition of discrete epitopes largely in the Gag protein, and expansion of IL-21+ CD4+ T cells in acute infection resulted in lower viral set points (P = 0.002). Moreover, IL-21 production by CD4+ T cells of HIV controllers enhanced perforin production by HIV-1-specific CD8+ T cells from chronic progressors even in late stages of disease, and HIV-1-specific effector CD8+ T cells showed an enhanced ability to efficiently inhibit viral replication in vitro after IL-21 binding. These data suggest that HIV-1-specific IL-21+ CD4+ T cell responses might contribute to the control of viral replication in humans and are likely to be of great importance for vaccine design. [ABSTRACT FROM AUTHOR]

Several human-adapted Mycobacterium tuberculosis complex (Mtbc) lineages exhibit a restricted geographical distribution globally. These lineages are hypothesized to transmit more effectively among sympatric hosts, that is, those that share the same geographical area, though this is yet to be confirmed while controlling for exposure, social networks and disease risk after exposure. Using pathogen genomic and contact tracing data from 2,279 tuberculosis cases linked to 12,749 contacts from three low-incidence cities, we show that geographically restricted Mtbc lineages were less transmissible than lineages that have a widespread global distribution. Allopatric host-pathogen exposure, in which the restricted pathogen and host are from non-overlapping areas, had a 38% decrease in the odds of infection among contacts compared with sympatric exposures. We measure tenfold lower uptake of geographically restricted lineage 6 strains compared with widespread lineage 4 strains in allopatric macrophage infections. We conclude that Mtbc strain-human long-term coexistence has resulted in differential transmissibility of Mtbc lineages and that this differs by human population., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Objectives: This study aimed to assess the consistency and replicability of treatment recommendations provided by ChatGPT 3.5 compared to gastrointestinal tumor cases presented at multidisciplinary tumor boards (MTBs). It also aimed to distinguish between general and case-specific responses and investigated the precision of ChatGPT's recommendations in replicating exact treatment plans, particularly regarding chemotherapy regimens and follow-up protocols., Material and Methods: A retrospective study was carried out on 115 cases of gastrointestinal malignancies, selected from 448 patients reviewed in MTB meetings. A senior resident fed patient data into ChatGPT 3.5 to produce treatment recommendations, which were then evaluated against the tumor board's decisions by senior oncology fellows., Results: Among the examined cases, ChatGPT 3.5 provided general information about the malignancy without considering individual patient characteristics in 19% of cases. However, only in 81% of cases, ChatGPT generated responses that were specific to the individual clinical scenarios. In the subset of case-specific responses, 83% of recommendations exhibited overall treatment strategy concordance between ChatGPT and MTB. However, the exact treatment concordance dropped to 65%, notably lower in recommending specific chemotherapy regimens. Cases recommended for surgery showed the highest concordance rates, while those involving chemotherapy recommendations faced challenges in precision., Conclusions: ChatGPT 3.5 demonstrates potential in aligning conceptual approaches to treatment strategies with MTB guidelines. However, it falls short in accurately duplicating specific treatment plans, especially concerning chemotherapy regimens and follow-up procedures. Ethical concerns and challenges in achieving exact replication necessitate prudence when considering ChatGPT 3.5 for direct clinical decision-making in MTBs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Global tuberculosis (TB) drug resistance (DR) surveillance focuses on rifampicin. We examined the potential of public and surveillance Mycobacterium tuberculosis ( Mtb ) whole-genome sequencing (WGS) data, to generate expanded country-level resistance prevalence estimates (antibiograms) using in silico resistance prediction., Methods: We curated and quality-controlled Mtb WGS data. We used a validated random forest model to predict phenotypic resistance to 12 drugs and bias-corrected for model performance, outbreak sampling and rifampicin resistance oversampling. Validation leveraged a national DR survey conducted in South Africa., Results: Mtb isolates from 29 countries (n=19 149) met sequence quality criteria. Global marginal genotypic resistance among mono-resistant TB estimates overlapped with the South African DR survey, except for isoniazid, ethionamide and second-line injectables, which were underestimated (n=3134). Among multidrug resistant (MDR) TB (n=268), estimates overlapped for the fluoroquinolones but overestimated other drugs. Globally pooled mono-resistance to isoniazid was 10.9% (95% CI: 10.2-11.7%, n=14 012). Mono-levofloxacin resistance rates were highest in South Asia (Pakistan 3.4% (0.1-11%), n=111 and India 2.8% (0.08-9.4%), n=114). Given the recent interest in drugs enhancing ethionamide activity and their expected activity against isolates with resistance discordance between isoniazid and ethionamide, we measured this rate and found it to be high at 74.4% (IQR: 64.5-79.7%) of isoniazid-resistant isolates predicted to be ethionamide susceptible. The global susceptibility rate to pyrazinamide and levofloxacin among MDR was 15.1% (95% CI: 10.2-19.9%, n=3964)., Conclusions: This is the first attempt at global Mtb antibiogram estimation. DR prevalence in Mtb can be reliably estimated using public WGS and phenotypic resistance prediction for key antibiotics, but public WGS data demonstrates oversampling of isolates with higher resistance levels than MDR. Nevertheless, our results raise concerns about the empiric use of short-course fluoroquinolone regimens for drug-susceptible TB in South Asia and indicate underutilisation of ethionamide in MDR treatment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Applying whole-genome-sequencing, we aimed to detect transmission events of multidrug-resistant/rifampin-resistant strains of Mycobacterium tuberculosis complex at a tuberculosis hospital in Chisinau, Moldova. We recorded ward, room, and bed information for each patient and monitored in-hospital transfers over 1 year. Detailed molecular and patient surveillance revealed only 2 nosocomial transmission events.

Digital health technologies can help tackle challenges in global public health. Digital and AI-for-Health Challenges, controlled events whose goal is to generate solutions to a given problem in a defined period of time, are one way of catalysing innovation. This article proposes an expanded investment framework for Global Health AI and digitalhealth Innovation that goes beyond traditional factors such as return on investment. Instead, we propose non monetary and non GDP metrics, such as Disability Adjusted Life Years or achievement of universal health coverage. Furthermore, we suggest a venture building approach around global health, which includes filtering of participants to reduce opportunity cost, close integration of implementation scientists and an incubator for the long-term development of ideas resulting from the challenge. Finally, we emphasize the need to strengthen human capital across a range of areas in local innovation, implementation-science, and in health services., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Farlow et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-based methods being considered the gold standard for drug susceptibility testing, molecular methods provide rapid information about the Mycobacterium tuberculosis mutations associated with resistance to anti-tuberculosis drugs. This consensus document was developed on the basis of a comprehensive literature search, by the TBnet and RESIST-TB networks, about reporting standards for the clinical use of molecular drug susceptibility testing. Review and the search for evidence included hand-searching journals and searching electronic databases. The panel identified studies that linked mutations in genomic regions of M tuberculosis with treatment outcome data. Implementation of molecular testing for the prediction of drug resistance in M tuberculosis is key. Detection of mutations in clinical isolates has implications for the clinical management of patients with multidrug-resistant or rifampicin-resistant tuberculosis, especially in situations when phenotypic drug susceptibility testing is not available. A multidisciplinary team including clinicians, microbiologists, and laboratory scientists reached a consensus on key questions relevant to molecular prediction of drug susceptibility or resistance to M tuberculosis, and their implications for clinical practice. This consensus document should help clinicians in the management of patients with tuberculosis, providing guidance for the design of treatment regimens and optimising outcomes., Competing Interests: Declaration of interests JD reports a technology licence to GenID (Germany), and honoraria for lectures from Oxford Immunotec (UK). EC reports support for attendance, accommodation, and travel for ECCMID 2022, Lisboa from European Society of Clinical Microbiology and Infectious Diseases (ESCMID), for annual ERL-TB net meetings from ERL-TB net (Network of National Reference Centers for Tuberculosis in Europe), and for the annual congress 2022, Bologna, from the European Society for Mycobacteriology; is a member of the Executive committee of ESCMID; and is chair of the subcommittee for antimycobacterial agents of EUCAST (European Committee on Antimicrobial Susceptibility Testing). MRF reports grants or contracts from NIH/NIAID (5R01AI155765 and 5R21AI154089) and consulting fees (paid to them) from FIND. LG is a member (unpaid) of the data safety monitoring board for the XACT-19 clinical trial in University of Cape Town, Cape Town, South Africa, and is co-principal investigator of two phase 3 clinical trials on shorter treatment for MDR-TB (endTB and endTB-Q), funded by Unitaid. BL reports grants or contracts from European Union, German Ministry for Education and Research (BMBF), Kultusministerkonferenz, German Centre for Infection Research, and Helmholtz Association, and unpaid leadership or fiduciary roles for DZIF IAB, DZIF Steering Committee transplant Cohort, and TBnet chair Epidemiology. SN reports support for this manuscript (eg, funding, provision of study materials, medical writing, and article processing charges) from BMBF (German Center for Infection Research), DFG (Excellenz Cluster Precision Medicine in Chronic Inflammation EXC 2167), and Leibniz Science Campus Evolutionary Medicine of the LUNG (EvoLUNG), and consulting fees from Illumina advisory board in 2022. NV reports grants or contracts for a study on bedaquiline from Janssen. CRH reports grants or contracts from NIH/NIAID (R01AI134430, DAA3-19-65672, R01AI147316 U01AI152980, and R01AI146555), and Centers for Disease Control and Prevention (NU38PS004651); consulting fees from Otsuka Pharmaceuticals; participation on a data safety monitoring board for SODUCU (PanACEA Sutezolid Dose-finding and Combination Evaluation), BEAT-Tuberculosis (Building Evidence for Advancing New treatment for tuberculosis), DECODE (PanACEA Delpazolid Dose-finding and Combination Development), and Médecins Sans Frontières; and a leadership or fiduciary role from the International Union Against Tuberculosis and Lung Diseases. CLa reports support for the present manuscript (eg, funding, provision of study materials, medical writing, and article processing charges) from DZIF (German Center of Infection Research); consulting fees from a consultation service to INSMED, a company that produced liposomal amikacin as an inhalative suspension for the treatment of non-tuberculous mycobacteria pulmonary disease (outside of the scope of this work); speakers' honoraria from Insmed, Gilead, and Janssen (all outside of the scope of this work); is a member of the data safety board of trials from Médecins Sans Frontières (outside of the scope of this work); is supported by the German Center for Infection Research (DZIF); and acknowledges funding from the European Commission (anTBiotic EU-H2020 733079, ClicTB EDCTP2 RIA2017T-2030, stool4TB EDCTP2 RIAD2018-2511, and UNITE4TB EU-IMI 101007873). All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: There is concern that the COVID-19 pandemic has damaged global childhood tuberculosis management. Quantifying changes in childhood tuberculosis notifications could support more targeted interventions to restore childhood tuberculosis services. We aimed to use time-series modelling to evaluate the impact of COVID-19 on child tuberculosis notifications., Methods: Annual tuberculosis case notification data reported to WHO by 215 countries were used to calculate annual notification counts for the years 2014-20, stratified by age groups (0-4, 5-14, and ≥15 years) and sex. We used time-series modelling to predict notification counts for 2020, and calculated differences between these predictions and observed notifications in 2020 for each of the six WHO regions and at the country level for 30 countries with high tuberculosis burden. We assessed associations between these differences and the COVID-19 stringency index, a measure of COVID-19 social impact., Findings: From 2014 to 2019, annual tuberculosis notification counts increased across all age groups and WHO regions. More males than females in the 0-4 years age group and ≥15 years age group had notifications in all years from 2014 to 2020 and in all WHO regions. In the 5-14 years age group, more females than males were notified globally in all years, although some WHO regions had higher notifications from males than females. In 2020, global notifications were 35·4% lower than predicted (95% prediction interval -30·3 to -39·9; 142 525 observed vs 220 794 predicted notifications [95% prediction interval 204 509 to 237 078]) for children aged 0-4 years, 27·7% lower (-23·4 to -31·5; 256 398 vs 354 578 [334 724 to 374 431]) in children aged 5-14 years, and 18·8% lower (-15·4 to -21·9; 5 391 753 vs 6 639 547 [6 375 086 to 6 904 007]) for people aged 15 years or older. Among those aged 5-14 years, the reduction in observed relative to predicted notifications for 2020 was greater in males (-30·9% [-24·8 to -36·1]) than females (-24·5% [-18·1 to -29·9]). Among 28 countries with high tuberculosis burden, no association was observed between the stringency of COVID-19 restrictions and the relative difference in observed versus predicted notifications., Interpretation: Our findings suggest that COVID-19 has substantially affected childhood tuberculosis services, with the youngest children most affected. Although children have mostly had fewer severe health consequences from COVID-19 than have adults, they have been disproportionately affected by the effects of the pandemic on tuberculosis care. Observed sex differences suggest that targeted interventions might be required. As countries rebuild health systems following the COVID-19 pandemic, it is crucial that childhood tuberculosis services are placed centrally within national strategic plans., Funding: Medical Research Council., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Artificial intelligence (AI) offers the potential to support healthcare delivery, but poorly trained or validated algorithms bear risks of harm. Ethical guidelines stated transparency about model development and validation as a requirement for trustworthy AI. Abundant guidance exists to provide transparency through reporting, but poorly reported medical AI tools are common. To close this transparency gap, we developed and piloted a framework to quantify the transparency of medical AI tools with three use cases. Our framework comprises a survey to report on the intended use, training and validation data and processes, ethical considerations, and deployment recommendations. The transparency of each response was scored with either 0, 0.5, or 1 to reflect if the requested information was not, partially, or fully provided. Additionally, we assessed on an analogous three-point scale if the provided responses fulfilled the transparency requirement for a set of trustworthiness criteria from ethical guidelines. The degree of transparency and trustworthiness was calculated on a scale from 0% to 100%. Our assessment of three medical AI use cases pin-pointed reporting gaps and resulted in transparency scores of 67% for two use cases and one with 59%. We report anecdotal evidence that business constraints and limited information from external datasets were major obstacles to providing transparency for the three use cases. The observed transparency gaps also lowered the degree of trustworthiness, indicating compliance gaps with ethical guidelines. All three pilot use cases faced challenges to provide transparency about medical AI tools, but more studies are needed to investigate those in the wider medical AI sector. Applying this framework for an external assessment of transparency may be infeasible if business constraints prevent the disclosure of information. New strategies may be necessary to enable audits of medical AI tools while preserving business secrets., Competing Interests: None of our team members were involved in the design of any of the reported medical AI use cases or employed by any of the reporting companies. M.B. is employed by Merck Group Pharma, but his involvement in this work was independent of his employment. He consulted the selection of survey questions and trustworthiness requirements from a scientific business administration perspective. M.B. was excluded from assessing the survey responses and had no access to the identities of the participants, their employing companies, and reported information. All other authors declare no conflicts of interest.

Long diagnostic wait times hinder international efforts to address antibiotic resistance in M. tuberculosis. Pathogen whole genome sequencing, coupled with statistical and machine learning models, offers a promising solution. However, generalizability and clinical adoption have been limited by a lack of interpretability, especially in deep learning methods. Here, we present two deep convolutional neural networks that predict antibiotic resistance phenotypes of M. tuberculosis isolates: a multi-drug CNN (MD-CNN), that predicts resistance to 13 antibiotics based on 18 genomic loci, with AUCs 82.6-99.5% and higher sensitivity than state-of-the-art methods; and a set of 13 single-drug CNNs (SD-CNN) with AUCs 80.1-97.1% and higher specificity than the previous state-of-the-art. Using saliency methods to evaluate the contribution of input sequence features to the SD-CNN predictions, we identify 18 sites in the genome not previously associated with resistance. The CNN models permit functional variant discovery, biologically meaningful interpretation, and clinical applicability., (© 2022. The Author(s).)

Background: 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., Results: 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 CONCLUSIONS: 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 ., (© 2021. The Author(s).)

Objectives: B-lines are a lung ultrasound (LUS) artifact that often indicate pathology. Little is known about the optimal ultrasound machine settings to assess B-lines. We compared settings typically used to evaluate B-lines at our institution with adjusted settings based on recent studies., Methods: In order to determine typical settings for B-line assessment, we retrospectively reviewed LUS images obtained at our institution. We then prospectively performed LUS with both typical and adjusted settings, using curvilinear and phased array probes, in 20 patients presenting to the emergency department with shortness of breath. The prospectively obtained clips were rated for quality and quantity of B-lines by 14 clinicians with experience in LUS, with 1 assigned for typical settings "much greater," 2 for typical settings "slightly greater," 3 for both settings "similar," 4 for adjusted settings "slightly greater," and 5 for adjusted settings "much greater.", Results: Mean ratings and 95% confidence intervals significantly exceeded the null value of 3 for both B line quality (curvilinear probe: 4.68, 4.50-4.85; phased array probe: 4.02, 3.70-4.35) and B line quantity (curvilinear probe: 4.16, 3.84-4.49; phased array probe: 3.68, 3.41-3.96)., Conclusions: B-line quality and quantity were rated higher using adjusted settings based on recently published evidence than when using settings that are typically employed in our institution. Our findings suggest that B-line assessment should be performed with focal zone at the level of the pleura, harmonics off, and gain increased in the far field., (© 2020 The Authors. Journal of Ultrasound in Medicine published by Wiley Periodicals LLC on behalf of American Institute of Ultrasound in Medicine.)

Stenotrophomonas maltophilia is one of the most frequently isolated multidrug-resistant nosocomial opportunistic pathogens. It contributes to disease progression in cystic fibrosis (CF) patients and is frequently isolated from wounds, infected tissues, and catheter surfaces. On these diverse surfaces S. maltophilia lives in single-species or multispecies biofilms. Since very little is known about common processes in biofilms of different S. maltophilia isolates, we analyzed the biofilm profiles of 300 clinical and environmental isolates from Europe of the recently identified main lineages Sgn3, Sgn4, and Sm2 to Sm18. The analysis of the biofilm architecture of 40 clinical isolates revealed the presence of multicellular structures and high phenotypic variability at a strain-specific level. Further, transcriptome analyses of biofilm cells of seven clinical isolates identified a set of 106 shared strongly expressed genes and 33 strain-specifically expressed genes. Surprisingly, the transcriptome profiles of biofilm versus planktonic cells revealed that just 9.43% ± 1.36% of all genes were differentially regulated. This implies that just a small set of shared and commonly regulated genes is involved in the biofilm lifestyle. Strikingly, iron uptake appears to be a key factor involved in this metabolic shift. Further, metabolic analyses implied that S. maltophilia employs a mostly fermentative growth mode under biofilm conditions. The transcriptome data of this study together with the phenotypic and metabolic analyses represent so far the largest data set on S. maltophilia biofilm versus planktonic cells. This study will lay the foundation for the identification of strategies for fighting S. maltophilia biofilms in clinical and industrial settings. IMPORTANCE Microorganisms living in a biofilm are much more tolerant to antibiotics and antimicrobial substances than planktonic cells are. Thus, the treatment of infections caused by microorganisms living in biofilms is extremely difficult. Nosocomial infections (among others) caused by S. maltophilia , particularly lung infection among CF patients, have increased in prevalence in recent years. The intrinsic multidrug resistance of S. maltophilia and the increased tolerance to antimicrobial agents of its biofilm cells make the treatment of S. maltophilia infection difficult. The significance of our research is based on understanding the common mechanisms involved in biofilm formation of different S. maltophilia isolates, understanding the diversity of biofilm architectures among strains of this species, and identifying the differently regulated processes in biofilm versus planktonic cells. These results will lay the foundation for the treatment of S. maltophilia biofilms., (Copyright © 2020 Alio et al.)

Accurate drug resistance detection is key for guiding effective tuberculosis treatment. While genotypic resistance can be rapidly detected by molecular methods, their application is challenged by mixed mycobacterial populations comprising both susceptible and resistant cells (heteroresistance). For this, next-generation sequencing (NGS) based approaches promise the determination of variants even at low frequencies. However, accurate methods for a valid detection of low-frequency variants in NGS data are currently lacking. To tackle this problem, we developed the variant detection tool binoSNP which allows the determination of low-frequency single nucleotide polymorphisms (SNPs) in NGS datasets from Mycobacterium tuberculosis complex (MTBC) strains. By taking a reference-mapped file as input, binoSNP evaluates each genomic position of interest using a binomial test procedure. binoSNP was validated using in-silico, in-vitro, and serial patient isolates datasets comprising varying genomic coverage depths (100-500×) and SNP allele frequencies (1-30%). Overall, the detection limit for low-frequency SNPs depends on the combination of coverage depth and allele frequency of the resistance-associated mutation. binoSNP allows for valid detection of resistance associated SNPs at a 1% frequency with a coverage ≥400×. In conclusion, binoSNP provides a valid approach to detect low-frequency resistance-mediating SNPs in NGS data from clinical MTBC strains. It can be implemented in automated, end-user friendly analysis tools for NGS data and is a step forward towards individualized TB therapy.