Anti-apoptotic Protein BIRC5 Maintains Survival of HIV-1-Infected CD4+ T Cells.

HIV-1 infection of CD4+ T cells leads to cytopathic effects and cell demise, which is counter to the observation that certain HIV-1-infected cells possess a remarkable long-term stability and can persist lifelong in infected individuals treated with suppressive antiretroviral therapy (ART). Using quantitative mass spectrometry-based proteomics, we showed that HIV-1 infection activated cellular survival programs that were governed by BIRC5, a molecular inhibitor of cell apoptosis that is frequently overexpressed in malignant cells. BIRC5 and its upstream regulator OX40 were upregulated in productively and latently infected CD4+ T cells and were functionally involved in maintaining their viability. Moreover, OX40-expressing CD4+ T cells from ART-treated patients were enriched for clonally expanded HIV-1 sequences, and pharmacological inhibition of BIRC5 resulted in a selective decrease of HIV-1-infected cells in vitro. Together, these findings suggest that BIRC5 supports long-term survival of HIV-1-infected cells and may lead to clinical strategies to reduce persisting viral reservoirs.

Brain-specific deletion of GIT1 impairs cognition and alters phosphorylation of synaptic protein networks implicated in schizophrenia susceptibility.

Despite tremendous effort, the molecular and cellular basis of cognitive deficits in schizophrenia remain poorly understood. Recent progress in elucidating the genetic architecture of schizophrenia has highlighted the association of multiple loci and rare variants that may impact susceptibility. One key example, given their potential etiopathogenic and therapeutic relevance, is a set of genes that encode proteins that regulate excitatory glutamatergic synapses in brain. A critical next step is to delineate specifically how such genetic variation impacts synaptic plasticity and to determine if and how the encoded proteins interact biochemically with one another to control cognitive function in a convergent manner. Towards this goal, here we study the roles of GPCR-kinase interacting protein 1 (GIT1), a synaptic scaffolding and signaling protein with damaging coding variants found in schizophrenia patients, as well as copy number variants found in patients with neurodevelopmental disorders. We generated conditional neural-selective GIT1 knockout mice and found that these mice have deficits in fear conditioning memory recall and spatial memory, as well as reduced cortical neuron dendritic spine density. Using global quantitative phospho-proteomics, we revealed that GIT1 deletion in brain perturbs specific networks of GIT1-interacting synaptic proteins. Importantly, several schizophrenia and neurodevelopmental disorder risk genes are present within these networks. We propose that GIT1 regulates the phosphorylation of a network of synaptic proteins and other critical regulators of neuroplasticity, and that perturbation of these networks may contribute specifically to cognitive deficits observed in schizophrenia and neurodevelopmental disorders.

A review of the current state of single-cell proteomics and future perspective.

Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.

A Curated Resource for Phosphosite-specific Signature Analysis.

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

Small RNA profiling in Mycobacterium tuberculosis identifies MrsI as necessary for an anticipatory iron sparing response.

One key to the success of Mycobacterium tuberculosis as a pathogen is its ability to reside in the hostile environment of the human macrophage. Bacteria adapt to stress through a variety of mechanisms, including the use of small regulatory RNAs (sRNAs), which posttranscriptionally regulate bacterial gene expression. However, very little is currently known about mycobacterial sRNA-mediated riboregulation. To date, mycobacterial sRNA discovery has been performed primarily in log-phase growth, and no direct interaction between any mycobacterial sRNA and its targets has been validated. Here, we performed large-scale sRNA discovery and expression profiling in M. tuberculosis during exposure to five pathogenically relevant stresses. From these data, we identified a subset of sRNAs that are highly induced in multiple stress conditions. We focused on one of these sRNAs, ncRv11846, here renamed mycobacterial regulatory sRNA in iron (MrsI). We characterized the regulon of MrsI and showed in mycobacteria that it regulates one of its targets, bfrA, through a direct binding interaction. MrsI mediates an iron-sparing response that is required for optimal survival of M. tuberculosis under iron-limiting conditions. However, MrsI is induced by multiple host-like stressors, which appear to trigger MrsI as part of an anticipatory response to impending iron deprivation in the macrophage environment.

Comparison of Statistical Tests and Power Analysis for Phosphoproteomics Data.

Advances in protein tagging and mass spectrometry have enabled generation of large quantitative proteome and phosphoproteome data sets, for identifying differentially expressed targets in case-control studies. The power study of statistical tests is critical for designing strategies for effective target identification and control of experimental cost. Here, we develop a simulation framework to generate realistic phospho-peptide data with known changes between cases and controls. Using this framework, we quantify the performance of traditional t-tests, Bayesian tests, and the ranking-by-fold-change test. Bayesian tests, which share variance information among peptides, outperform the traditional t-tests. Although ranking-by-fold-change has similar power as the Bayesian tests, its type I error rate cannot be properly controlled without proper permutation analysis; therefore, simply relying on the ranking likely brings false positives. Two-sample Bayesian tests considering dependencies between intensity and variance are superior for data sets with complex variance. While increasing the sample size enhances the statistical tests' performance, balanced controls and cases are recommended over a one-side weighted group. Further, higher peptide standard deviations require higher fold changes to achieve the same statistical power. Together, these results highlight the importance of model-informed experimental design and principled statistical analyses when working with large-scale proteomics and phosphoproteomics data.

Quantitative Proteomic Profiling Reveals Novel Plasmodium falciparum Surface Antigens and Possible Vaccine Candidates.

Despite recent efforts toward control and elimination, malaria remains a major public health problem worldwide. Plasmodium falciparum resistance against artemisinin, used in front line combination drugs, is on the rise, and the only approved vaccine shows limited efficacy. Combinations of novel and tailored drug and vaccine interventions are required to maintain the momentum of the current malaria elimination program. Current evidence suggests that strain-transcendent protection against malaria infection can be achieved using whole organism vaccination or with a polyvalent vaccine covering multiple antigens or epitopes. These approaches have been successfully applied to the human-infective sporozoite stage. Both systemic and tissue-specific pathology during infection with the human malaria parasite P. falciparum is caused by asexual blood stages. Tissue tropism and vascular sequestration are the result of specific binding interactions between antigens on the parasite-infected red blood cell (pRBC) surface and endothelial receptors. The major surface antigen and parasite ligand binding to endothelial receptors, PfEMP1 is encoded by about 60 variants per genome and shows high sequence diversity across strains. Apart from PfEMP1 and three additional variant surface antigen families RIFIN, STEVOR, and SURFIN, systematic analysis of the infected red blood cell surface is lacking. Here we present the most comprehensive proteomic investigation of the parasitized red blood cell surface so far. Apart from the known variant surface antigens, we identified a set of putative single copy surface antigens with low sequence diversity, several of which are validated in a series of complementary experiments. Further functional and immunological investigation is underway to test these novel P. falciparum blood stage proteins as possible vaccine candidates.

Harnessing single-cell genomics to improve the physiological fidelity of organoid-derived cell types.

BACKGROUND: Single-cell genomic methods now provide unprecedented resolution for characterizing the component cell types and states of tissues such as the epithelial subsets of the gastrointestinal tract. Nevertheless, functional studies of these subsets at scale require faithful in vitro models of identified in vivo biology. While intestinal organoids have been invaluable in providing mechanistic insights in vitro, the extent to which organoid-derived cell types recapitulate their in vivo counterparts remains formally untested, with no systematic approach for improving model fidelity. RESULTS: Here, we present a generally applicable framework that utilizes massively parallel single-cell RNA-seq to compare cell types and states found in vivo to those of in vitro models such as organoids. Furthermore, we leverage identified discrepancies to improve model fidelity. Using the Paneth cell (PC), which supports the stem cell niche and produces the largest diversity of antimicrobials in the small intestine, as an exemplar, we uncover fundamental gene expression differences in lineage-defining genes between in vivo PCs and those of the current in vitro organoid model. With this information, we nominate a molecular intervention to rationally improve the physiological fidelity of our in vitro PCs. We then perform transcriptomic, cytometric, morphologic and proteomic characterization, and demonstrate functional (antimicrobial activity, niche support) improvements in PC physiology. CONCLUSIONS: Our systematic approach provides a simple workflow for identifying the limitations of in vitro models and enhancing their physiological fidelity. Using adult stem cell-derived PCs within intestinal organoids as a model system, we successfully benchmark organoid representation, relative to that in vivo, of a specialized cell type and use this comparison to generate a functionally improved in vitro PC population. We predict that the generation of rationally improved cellular models will facilitate mechanistic exploration of specific disease-associated genes in their respective cell types.

Leaderless Transcripts and Small Proteins Are Common Features of the Mycobacterial Translational Landscape.

RNA-seq technologies have provided significant insight into the transcription networks of mycobacteria. However, such studies provide no definitive information on the translational landscape. Here, we use a combination of high-throughput transcriptome and proteome-profiling approaches to more rigorously understand protein expression in two mycobacterial species. RNA-seq and ribosome profiling in Mycobacterium smegmatis, and transcription start site (TSS) mapping and N-terminal peptide mass spectrometry in Mycobacterium tuberculosis, provide complementary, empirical datasets to examine the congruence of transcription and translation in the Mycobacterium genus. We find that nearly one-quarter of mycobacterial transcripts are leaderless, lacking a 5' untranslated region (UTR) and Shine-Dalgarno ribosome-binding site. Our data indicate that leaderless translation is a major feature of mycobacterial genomes and is comparably robust to leadered initiation. Using translational reporters to systematically probe the cis-sequence requirements of leaderless translation initiation in mycobacteria, we find that an ATG or GTG at the mRNA 5' end is both necessary and sufficient. This criterion, together with our ribosome occupancy data, suggests that mycobacteria encode hundreds of small, unannotated proteins at the 5' ends of transcripts. The conservation of small proteins in both mycobacterial species tested suggests that some play important roles in mycobacterial physiology. Our translational-reporter system further indicates that mycobacterial leadered translation initiation requires a Shine Dalgarno site in the 5' UTR and that ATG, GTG, TTG, and ATT codons can robustly initiate translation. Our combined approaches provide the first comprehensive view of mycobacterial gene structures and their non-canonical mechanisms of protein expression.

Transcriptional Categorization of the Etiology of Pneumonia Syndrome in Pediatric Patients in Malaria-Endemic Areas.

Background: Pediatric acute respiratory distress in tropical settings is very common. Bacterial pneumonia is a major contributor to morbidity and mortality rates and requires adequate diagnosis for correct treatment. A rapid test that could identify bacterial (vs other) infections would have great clinical utility. Methods and Results: We performed RNA (RNA-seq) sequencing and analyzed the transcriptomes of 68 pediatric patients with well-characterized clinical phenotype to identify transcriptional features associated with each disease class. We refined the features to predictive models (support vector machine, elastic net) and validated those models in an independent test set of 37 patients (80%-85% accuracy). Conclusions: We have identified sets of genes that are differentially expressed in pediatric patients with pneumonia syndrome attributable to different infections and requiring different therapeutic interventions. Findings of this study demonstrate that human transcription signatures in infected patients recapitulate the underlying biology and provide models for predicting a bacterial diagnosis to inform treatment.

Responses to Bacteria, Virus, and Malaria Distinguish the Etiology of Pediatric Clinical Pneumonia.

RATIONALE: Plasma-detectable biomarkers that rapidly and accurately diagnose bacterial infections in children with suspected pneumonia could reduce the morbidity of respiratory disease and decrease the unnecessary use of antibiotic therapy. OBJECTIVES: Using 56 markers measured in a multiplexed immunoassay, we sought to identify proteins and protein combinations that could discriminate bacterial from viral or malarial diagnoses. METHODS: We selected 80 patients with clinically diagnosed pneumonia (as defined by the World Health Organization) who also met criteria for bacterial, viral, or malarial infection based on clinical, radiographic, and laboratory results. Ten healthy community control subjects were enrolled to assess marker reliability. Patients were subdivided into two sets: one for identifying potential markers and another for validating them. MEASUREMENTS AND MAIN RESULTS: Three proteins (haptoglobin, tumor necrosis factor receptor 2 or IL-10, and tissue inhibitor of metalloproteinases 1) were identified that, when combined through a classification tree signature, accurately classified patients into bacterial, malarial, and viral etiologies and misclassified only one patient with bacterial pneumonia from the validation set. The overall sensitivity and specificity of this signature for the bacterial diagnosis were 96 and 86%, respectively. Alternative combinations of markers with comparable accuracy were selected by support vector machine and regression models and included haptoglobin, IL-10, and creatine kinase-MB. CONCLUSIONS: Combinations of plasma proteins accurately identified children with a respiratory syndrome who were likely to have bacterial infections and who would benefit from antibiotic therapy. When used in conjunction with malaria diagnostic tests, they may improve diagnostic specificity and simplify treatment decisions for clinicians.

A framework for installable external tools in Skyline.

UNLABELLED: Skyline is a Windows client application for targeted proteomics method creation and quantitative data analysis. The Skyline document model contains extensive mass spectrometry data from targeted proteomics experiments performed using selected reaction monitoring, parallel reaction monitoring and data-independent and data-dependent acquisition methods. Researchers have developed software tools that perform statistical analysis of the experimental data contained within Skyline documents. The new external tools framework allows researchers to integrate their tools into Skyline without modifying the Skyline codebase. Installed tools provide point-and-click access to downstream statistical analysis of data processed in Skyline. The framework also specifies a uniform interface to format tools for installation into Skyline. Tool developers can now easily share their tools with proteomics researchers using Skyline. AVAILABILITY AND IMPLEMENTATION: Skyline is available as a single-click self-updating web installation at http://skyline.maccosslab.org. This Web site also provides access to installable external tools and documentation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High reliability in respiratory rate assessment in children with respiratory symptomatology in a rural area in Mozambique.

Early recognition of severe medical conditions is often based on clinical scores and vital sign measurements such as the respiratory rate (RR) count. We designed this study to determine the reliability of RR assessment counted three times during a full minute by independent observers in children in a developing country setting. A total of 55 participants were enrolled in the study. Participant ages ranged from 10 days to 7 years (median 22 months). Agreement for RR count was high (intraclass correlation coefficient of 0.95; 95% confidence interval: 0.93-0.97). Agreement for presence of tachypnea was also high (Kappa coefficient of 0.83, p < 0.001). However, a single reading would have misclassified 5-11% of the participants as non-tachypneic. Repeated RR counts offer reliable results if done during a full minute. Patients not fulfilling tachypnea criterion but with a high RR count should have the measurement repeated.

Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow.

With advances in sample preparation, small-volume liquid dispensing technologies, high-resolution MS/MS instrumentation, and data acquisition methodologies, it has become increasingly possible to confidently investigate the heterogeneous proteome found within individual cells. In this chapter, we present an automated high-throughput sample preparation workflow based on the Tecan Uno instrument for quantitative single-cell mass spectrometry-based proteomics. Cells are analyzed by the Single-Cell Proteome Analysis platform (SCREEN), which was introduced earlier and provides deeper proteome coverage across single cells.

Astrocyte elevated gene-1 promotes hepatocarcinogenesis: novel insights from a mouse model.

UNLABELLED: Astrocyte elevated gene-1 (AEG-1) is a key contributor to hepatocellular carcinoma (HCC) development and progression. To enhance our understanding of the role of AEG-1 in hepatocarcinogenesis, a transgenic mouse with hepatocyte-specific expression of AEG-1 (Alb/AEG1) was developed. Treating Alb/AEG-1, but not wild-type (WT) mice, with N-nitrosodiethylamine resulted in multinodular HCC with steatotic features and associated modulation of expression of genes regulating invasion, metastasis, angiogenesis, and fatty acid synthesis. Hepatocytes isolated from Alb/AEG-1 mice displayed profound resistance to chemotherapeutics and growth factor deprivation with activation of prosurvival signaling pathways. Alb/AEG-1 hepatocytes also exhibited marked resistance toward senescence, which correlated with abrogation of activation of a DNA damage response. Conditioned media from Alb/AEG-1 hepatocytes induced marked angiogenesis with elevation in several coagulation factors. Among these factors, AEG-1 facilitated the association of factor XII (FXII) messenger RNA with polysomes, resulting in increased translation. Short interfering RNA-mediated knockdown of FXII resulted in profound inhibition of AEG-1-induced angiogenesis. CONCLUSION: We uncovered novel aspects of AEG-1 functions, including induction of steatosis, inhibition of senescence, and activation of the coagulation pathway to augment aggressive hepatocarcinogenesis. The Alb/AEG-1 mouse provides an appropriate model to scrutinize the molecular mechanism of hepatocarcinogenesis and to evaluate the efficacy of novel therapeutic strategies targeting HCC.

Biofabrication of Multiplexed Electrochemical Immunosensors for Simultaneous Detection of Clinical Biomarkers in Complex Fluids.

Simultaneous detection of multiple disease biomarkers in unprocessed whole blood is considered the gold standard for accurate clinical diagnosis. Here, this study reports the development of a 4-plex electrochemical (EC) immunosensor with on-chip negative control capable of detecting a range of biomarkers in small volumes (15 µL) of complex biological fluids, including serum, plasma, and whole blood. A framework for fabricating and optimizing multiplexed sandwich immunoassays is presented that is enabled by use of EC sensor chips coated with an ultra-selective, antifouling, and nanocomposite coating. Cyclic voltammetry evaluation of sensor performance is carried out by monitoring the local precipitation of an electroactive product generated by horseradish peroxidase linked to a secondary antibody. EC immunosensors demonstrate high sensitivity and specificity without background signal with a limit of detection in single-digit picogram per milliliter in multiple complex biological fluids. These multiplexed immunosensors enable the simultaneous detection of four different biomarkers in plasma and whole blood with excellent sensitivity and selectivity. This rapid and cost-effective biosensor platform can be further adapted for use with different high affinity probes for any biomarker, and thereby create for a new class of highly sensitive and specific multiplexed diagnostics.

Neurogranin, Encoded by the Schizophrenia Risk Gene NRGN, Bidirectionally Modulates Synaptic Plasticity via Calmodulin-Dependent Regulation of the Neuronal Phosphoproteome.

BACKGROUND: Neurogranin (Ng), encoded by the schizophrenia risk gene NRGN, is a calmodulin-binding protein enriched in the postsynaptic compartments, and its expression is reduced in the postmortem brains of patients with schizophrenia. Experience-dependent translation of Ng is critical for encoding contextual memory, and Ng regulates developmental plasticity in the primary visual cortex during the critical period. However, the overall impact of Ng on the neuronal signaling that regulates synaptic plasticity is unknown. METHODS: Altered Ng expression was achieved via virus-mediated gene manipulation in mice. The effect on long-term potentiation (LTP) was accessed using spike timing-dependent plasticity protocols. Quantitative phosphoproteomics analyses led to discoveries in significant phosphorylated targets. An identified candidate was examined with high-throughput planar patch clamp and was validated with pharmacological manipulation. RESULTS: Ng bidirectionally modulated LTP in the hippocampus. Decreasing Ng levels significantly affected the phosphorylation pattern of postsynaptic density proteins, including glutamate receptors, GTPases, kinases, RNA binding proteins, selective ion channels, and ionic transporters, some of which highlighted clusters of schizophrenia- and autism-related genes. Hypophosphorylation of NMDA receptor subunit Grin2A, one significant phosphorylated target, resulted in accelerated decay of NMDA receptor currents. Blocking protein phosphatase PP2B activity rescued the accelerated NMDA receptor current decay and the impairment of LTP mediated by Ng knockdown, implicating the requirement of synaptic PP2B activity for the deficits. CONCLUSIONS: Altered Ng levels affect the phosphorylation landscape of neuronal proteins. PP2B activity is required for mediating the deficit in synaptic plasticity caused by decreasing Ng levels, revealing a novel mechanistic link of a schizophrenia risk gene to cognitive deficits.

Optimizing performance of glycopeptide capture for plasma proteomics.

Selective capture of glycopolypeptides followed by release and analysis of the former glycosylation-site peptides has been shown to have promise for reducing the complexity of body fluids such as blood for biomarker discovery. In this work, a protocol based on capture of polypeptides containing a N-linked carbohydrate from human plasma using commercially available magnetic beads coupled with hydrazide chemistry was optimized and partially automated through the use of a KingFisher magnetic particle processor. Comparison of bead-based glycocapture at the protein-level vs the peptide-level revealed differences in the specificity, reproducibility, and absolute number of former glycosylation-site peptides detected. Evaluation of a range of capture and elution conditions led to an optimized protocol with a 24% intraday and 30% interday CV and a glycopeptide capture specificity of 99%. Depleting the plasma of 14 high abundance proteins improved detection sensitivity by approximately 1 order of magnitude compared to nondepleted plasma and resulted in an increase of 24% in the number of identified glycoproteins. The sensitivity of SPEG for detection of glycoproteins in depleted, non-fractionated plasma was found to be in the 10-100 pmol/mL range corresponding to glycoprotein levels ranging from 100's of nanograms/mL to 10's of micrograms/mL. Despite high capture specificity, the total number of glycoproteins detected and the sensitivity of SPEG in plasma is surprisingly limited.

A rapid triage test for active pulmonary tuberculosis in adult patients with persistent cough.

Improved tuberculosis (TB) prevention and control depend critically on the development of a simple, readily accessible rapid triage test to stratify TB risk. We hypothesized that a blood protein-based host response signature for active TB (ATB) could distinguish it from other TB-like disease (OTD) in adult patients with persistent cough, thereby providing a foundation for a point-of-care (POC) triage test for ATB. Three adult cohorts consisting of ATB suspects were recruited. A bead-based immunoassay and machine learning algorithms identified a panel of four host blood proteins, interleukin-6 (IL-6), IL-8, IL-18, and vascular endothelial growth factor (VEGF), that distinguished ATB from OTD. An ultrasensitive POC-amenable single-molecule array (Simoa) panel was configured, and the ATB diagnostic algorithm underwent blind validation in an independent, multinational cohort in which ATB was distinguished from OTD with receiver operator characteristic-area under the curve (ROC-AUC) of 0.80 [95% confidence interval (CI), 0.75 to 0.85], 80% sensitivity (95% CI, 73 to 85%), and 65% specificity (95% CI, 57 to 71%). When host antibodies against TB antigen Ag85B were added to the panel, performance improved to 86% sensitivity and 69% specificity. A blood-based host response panel consisting of four proteins and antibodies to one TB antigen can help to differentiate ATB from other causes of persistent cough in patients with and without HIV infection from Africa, Asia, and South America. Performance characteristics approach World Health Organization (WHO) target product profile accuracy requirements and may provide the foundation for an urgently needed blood-based POC TB triage test.

Ribosomal mutations promote the evolution of antibiotic resistance in a multidrug environment.

Antibiotic resistance arising via chromosomal mutations is typically specific to a particular antibiotic or class of antibiotics. We have identified mutations in genes encoding ribosomal components in Mycobacterium smegmatis that confer resistance to several structurally and mechanistically unrelated classes of antibiotics and enhance survival following heat shock and membrane stress. These mutations affect ribosome assembly and cause large-scale transcriptomic and proteomic changes, including the downregulation of the catalase KatG, an activating enzyme required for isoniazid sensitivity, and upregulation of WhiB7, a transcription factor involved in innate antibiotic resistance. Importantly, while these ribosomal mutations have a fitness cost in antibiotic-free medium, in a multidrug environment they promote the evolution of high-level, target-based resistance. Further, suppressor mutations can then be easily acquired to restore wild-type growth. Thus, ribosomal mutations can serve as stepping-stones in an evolutionary path leading to the emergence of high-level, multidrug resistance.