Early cellular mechanisms of type I interferon-driven susceptibility to tuberculosis.

Mycobacterium tuberculosis (Mtb) causes 1.6 million deaths annually. Active tuberculosis correlates with a neutrophil-driven type I interferon (IFN) signature, but the cellular mechanisms underlying tuberculosis pathogenesis remain poorly understood. We found that interstitial macrophages (IMs) and plasmacytoid dendritic cells (pDCs) are dominant producers of type I IFN during Mtb infection in mice and non-human primates, and pDCs localize near human Mtb granulomas. Depletion of pDCs reduces Mtb burdens, implicating pDCs in tuberculosis pathogenesis. During IFN-driven disease, we observe abundant DNA-containing neutrophil extracellular traps (NETs) described to activate pDCs. Cell-type-specific disruption of the type I IFN receptor suggests that IFNs act on IMs to inhibit Mtb control. Single-cell RNA sequencing (scRNA-seq) indicates that type I IFN-responsive cells are defective in their response to IFNγ, a cytokine critical for Mtb control. We propose that pDC-derived type I IFNs act on IMs to permit bacterial replication, driving further neutrophil recruitment and active tuberculosis disease.

The cellular architecture of the antimicrobial response network in human leprosy granulomas.

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1ß. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control.

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

BHLHE40 Regulates Myeloid Cell Polarization through IL-10-Dependent and -Independent Mechanisms.

Better understanding of the host responses to Mycobacterium tuberculosis infections is required to prevent tuberculosis and develop new therapeutic interventions. The host transcription factor BHLHE40 is essential for controlling M. tuberculosis infection, in part by repressing Il10 expression, where excess IL-10 contributes to the early susceptibility of Bhlhe40-/- mice to M. tuberculosis infection. Deletion of Bhlhe40 in lung macrophages and dendritic cells is sufficient to increase the susceptibility of mice to M. tuberculosis infection, but how BHLHE40 impacts macrophage and dendritic cell responses to M. tuberculosis is unknown. In this study, we report that BHLHE40 is required in myeloid cells exposed to GM-CSF, an abundant cytokine in the lung, to promote the expression of genes associated with a proinflammatory state and better control of M. tuberculosis infection. Loss of Bhlhe40 expression in murine bone marrow-derived myeloid cells cultured in the presence of GM-CSF results in lower levels of proinflammatory associated signaling molecules IL-1ß, IL-6, IL-12, TNF-α, inducible NO synthase, IL-2, KC, and RANTES, as well as higher levels of the anti-inflammatory-associated molecules MCP-1 and IL-10 following exposure to heat-killed M. tuberculosis. Deletion of Il10 in Bhlhe40-/- myeloid cells restored some, but not all, proinflammatory signals, demonstrating that BHLHE40 promotes proinflammatory responses via both IL-10-dependent and -independent mechanisms. In addition, we show that macrophages and neutrophils within the lungs of M. tuberculosis-infected Bhlhe40-/- mice exhibit defects in inducible NO synthase production compared with infected wild-type mice, supporting that BHLHE40 promotes proinflammatory responses in innate immune cells, which may contribute to the essential role for BHLHE40 during M. tuberculosis infection in vivo.

Contrastive learning in protein language space predicts interactions between drugs and protein targets.

Sequence-based prediction of drug-target interactions has the potential to accelerate drug discovery by complementing experimental screens. Such computational prediction needs to be generalizable and scalable while remaining sensitive to subtle variations in the inputs. However, current computational techniques fail to simultaneously meet these goals, often sacrificing performance of one to achieve the others. We develop a deep learning model, ConPLex, successfully leveraging the advances in pretrained protein language models ("PLex") and employing a protein-anchored contrastive coembedding ("Con") to outperform state-of-the-art approaches. ConPLex achieves high accuracy, broad adaptivity to unseen data, and specificity against decoy compounds. It makes predictions of binding based on the distance between learned representations, enabling predictions at the scale of massive compound libraries and the human proteome. Experimental testing of 19 kinase-drug interaction predictions validated 12 interactions, including four with subnanomolar affinity, plus a strongly binding EPHB1 inhibitor (KD = 1.3 nM). Furthermore, ConPLex embeddings are interpretable, which enables us to visualize the drug-target embedding space and use embeddings to characterize the function of human cell-surface proteins. We anticipate that ConPLex will facilitate efficient drug discovery by making highly sensitive in silico drug screening feasible at the genome scale. ConPLex is available open source at https://ConPLex.csail.mit.edu.

MEK inhibition enhances presentation of targetable MHC-I tumor antigens in mutant melanomas.

Combining multiple therapeutic strategies in NRAS/BRAF mutant melanoma-namely MEK/BRAF kinase inhibitors, immune checkpoint inhibitors (ICIs), and targeted immunotherapies-may offer an improved survival benefit by overcoming limitations associated with any individual therapy. Still, optimal combination, order, and timing of administration remains under investigation. Here, we measure how MEK inhibition (MEKi) alters anti-tumor immunity by utilizing quantitative immunopeptidomics to profile changes in the peptide major histocompatibility molecules (pMHC) repertoire. These data reveal a collection of tumor antigens whose presentation levels are selectively augmented following therapy, including several epitopes present at over 1,000 copies per cell. We leveraged the tunable abundance of MEKi-modulated antigens by targeting four epitopes with pMHC-specific T cell engagers and antibody drug conjugates, enhancing cell killing in tumor cells following MEK inhibition. These results highlight drug treatment as a means to enhance immunotherapy efficacy by targeting specific upregulated pMHCs and provide a methodological framework for identifying, quantifying, and therapeutically targeting additional epitopes of interest.

Selective Glycan Labeling of Mannose-Containing Glycolipids in Mycobacteria.

Mycobacterium tuberculosis (Mtb) is one of history's most successful human pathogens. By subverting typical immune responses, Mtb can persist within a host until conditions become favorable for growth and proliferation. Virulence factors that enable mycobacteria to modulate host immune systems include a suite of mannose-containing glycolipids: phosphatidylinositol mannosides, lipomannan, and lipoarabinomannan (LAM). Despite their importance, tools for their covalent capture, modification, and imaging are limited. Here, we describe a chemical biology strategy to detect and visualize these glycans. Our approach, biosynthetic incorporation, is to synthesize a lipid-glycan precursor that can be incorporated at a late-stage step in glycolipid biosynthesis. We previously demonstrated selective mycobacterial arabinan modification by biosynthetic incorporation using an exogenous donor. This report reveals that biosynthetic labeling is general and selective: it allows for cell surface mannose-containing glycolipid modification without nonspecific labeling of mannosylated glycoproteins. Specifically, we employed azido-(Z,Z)-farnesyl phosphoryl-ß-d-mannose probes and took advantage of the strain-promoted azide-alkyne cycloaddition to label and directly visualize the localization and dynamics of mycobacterial mannose-containing glycolipids. Our studies highlight the generality and utility of biosynthetic incorporation as the probe structure directs the selective labeling of distinct glycans. The disclosed agents allowed for direct tracking of the target immunomodulatory glycolipid dynamics in cellulo. We anticipate that these probes will facilitate investigating the diverse biological roles of these glycans.

Biosynthetic Glycan Labeling.

Glycans are ubiquitous and play important biological roles, yet chemical methods for probing their structure and function within cells remain limited. Strategies for studying other biomacromolecules, such as proteins, often exploit chemoselective reactions for covalent modification, capture, or imaging. Unlike amino acids that constitute proteins, glycan building blocks lack distinguishing reactivity because they are composed primarily of polyol isomers. Moreover, encoding glycan variants through genetic manipulation is complex. Therefore, we formulated a new, generalizable strategy for chemoselective glycan modification that directly takes advantage of cellular glycosyltransferases. Many of these enzymes are selective for the products they generate yet promiscuous in their donor preferences. Thus, we designed reagents with bioorthogonal handles that function as glycosyltransferase substrate surrogates. We validated the feasibility of this approach by synthesizing and testing probes of d-arabinofuranose (d-Araf), a monosaccharide found in bacteria and an essential component of the cell wall that protects mycobacteria, including Mycobacterium tuberculosis. The result is the first probe capable of selectively labeling arabinofuranose-containing glycans. Our studies serve as a platform for developing new chemoselective labeling agents for other privileged monosaccharides. This probe revealed an asymmetric distribution of d-Araf residues during mycobacterial cell growth and could be used to detect mycobacteria in THP1-derived macrophages.

IL-1ß Induces the Rapid Secretion of the Antimicrobial Protein IL-26 from Th17 Cells.

Th17 cells play a critical role in the adaptive immune response against extracellular bacteria, and the possible mechanisms by which they can protect against infection are of particular interest. In this study, we describe, to our knowledge, a novel IL-1ß dependent pathway for secretion of the antimicrobial peptide IL-26 from human Th17 cells that is independent of and more rapid than classical TCR activation. We find that IL-26 is secreted 3 hours after treating PBMCs with Mycobacterium leprae as compared with 48 hours for IFN-γ and IL-17A. IL-1ß was required for microbial ligand induction of IL-26 and was sufficient to stimulate IL-26 release from Th17 cells. Only IL-1RI+ Th17 cells responded to IL-1ß, inducing an NF-κB-regulated transcriptome. Finally, supernatants from IL-1ß-treated memory T cells killed Escherichia coli in an IL-26-dependent manner. These results identify a mechanism by which human IL-1RI+ "antimicrobial Th17 cells" can be rapidly activated by IL-1ß as part of the innate immune response to produce IL-26 to kill extracellular bacteria.

Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.

Single-cell RNA-seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA-seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We use Seq-Well to profile thousands of primary human macrophages exposed to Mycobacterium tuberculosis.

The bromodomain protein Brd4 insulates chromatin from DNA damage signalling.

DNA damage activates a signalling network that blocks cell-cycle progression, recruits DNA repair factors and/or triggers senescence or programmed cell death. Alterations in chromatin structure are implicated in the initiation and propagation of the DNA damage response. Here we further investigate the role of chromatin structure in the DNA damage response by monitoring ionizing-radiation-induced signalling and response events with a high-content multiplex RNA-mediated interference screen of chromatin-modifying and -interacting genes. We discover that an isoform of Brd4, a bromodomain and extra-terminal (BET) family member, functions as an endogenous inhibitor of DNA damage response signalling by recruiting the condensin II chromatin remodelling complex to acetylated histones through bromodomain interactions. Loss of this isoform results in relaxed chromatin structure, rapid cell-cycle checkpoint recovery and enhanced survival after irradiation, whereas functional gain of this isoform compacted chromatin, attenuated DNA damage response signalling and enhanced radiation-induced lethality. These data implicate Brd4, previously known for its role in transcriptional control, as an insulator of chromatin that can modulate the signalling response to DNA damage.

SirT1 is required in the male germ cell for differentiation and fecundity in mice.

Sirtuins are NAD(+)-dependent deacylases that regulate numerous biological processes in response to the environment. SirT1 is the mammalian ortholog of yeast Sir2, and is involved in many metabolic pathways in somatic tissues. Whole body deletion of SirT1 alters reproductive function in oocytes and the testes, in part caused by defects in central neuro-endocrine control. To study the function of SirT1 specifically in the male germ line, we deleted this sirtuin in male germ cells and found that mutant mice had smaller testes, a delay in differentiation of pre-meiotic germ cells, decreased spermatozoa number, an increased proportion of abnormal spermatozoa and reduced fertility. At the molecular level, mutants do not have the characteristic increase in acetylation of histone H4 at residues K5, K8 and K12 during spermiogenesis and demonstrate corresponding defects in the histone to protamine transition. Our findings thus reveal a germ cell-autonomous role of SirT1 in spermatogenesis.

Variability in tuberculosis granuloma T cell responses exists, but a balance of pro- and anti-inflammatory cytokines is associated with sterilization.

Lung granulomas are the pathologic hallmark of tuberculosis (TB). T cells are a major cellular component of TB lung granulomas and are known to play an important role in containment of Mycobacterium tuberculosis (Mtb) infection. We used cynomolgus macaques, a non-human primate model that recapitulates human TB with clinically active disease, latent infection or early infection, to understand functional characteristics and dynamics of T cells in individual granulomas. We sought to correlate T cell cytokine response and bacterial burden of each granuloma, as well as granuloma and systemic responses in individual animals. Our results support that each granuloma within an individual host is independent with respect to total cell numbers, proportion of T cells, pattern of cytokine response, and bacterial burden. The spectrum of these components overlaps greatly amongst animals with different clinical status, indicating that a diversity of granulomas exists within an individual host. On average only about 8% of T cells from granulomas respond with cytokine production after stimulation with Mtb specific antigens, and few "multi-functional" T cells were observed. However, granulomas were found to be "multi-functional" with respect to the combinations of functional T cells that were identified among lesions from individual animals. Although the responses generally overlapped, sterile granulomas had modestly higher frequencies of T cells making IL-17, TNF and any of T-1 (IFN-γ, IL-2, or TNF) and/or T-17 (IL-17) cytokines than non-sterile granulomas. An inverse correlation was observed between bacterial burden with TNF and T-1/T-17 responses in individual granulomas, and a combinatorial analysis of pair-wise cytokine responses indicated that granulomas with T cells producing both pro- and anti-inflammatory cytokines (e.g. IL-10 and IL-17) were associated with clearance of Mtb. Preliminary evaluation suggests that systemic responses in the blood do not accurately reflect local T cell responses within granulomas.

RNA Extraction from a Mycobacterium under Ultrahigh Electric Field Intensity in a Microfluidic Device.

Studies of transcriptomes are critical for understanding gene expression. Release of RNA molecules from cells is typically the first step for transcriptomic analysis. Effective cell lysis approaches that completely release intracellular materials are in high demand especially for cells that are structurally robust. In this report, we demonstrate a microfluidic electric lysis device that is effective for mRNA extraction from mycobacteria that have hydrophobic and waxy cell walls. We used a packed bed of microscale silica beads to filter M. smegmatis out of the suspension. 4000-8000 V/cm field intensity was used to lyse M. smegmatis with long pulses (i.e., up to 30 pulses that were 5 s long each). Our quantitative reverse transcription (qRT)-PCR results showed that our method yielded a factor of 10-20 higher extraction efficiency than the current state-of-the-art method (bead beating). We conclude that our electric lysis technique is an effective approach for mRNA release from hard-to-lyse cells and highly compatible with microfluidic molecular assays.

Engineered bromodomains to explore the acetylproteome.

MS-based analysis of the acetylproteome has highlighted a role for acetylation in a wide array of biological processes including gene regulation, metabolism, and cellular signaling. To date, anti-acetyllysine antibodies have been used as the predominant affinity reagent for enrichment of acetyllysine-containing peptides and proteins; however, these reagents suffer from high nonspecific binding and lot-to-lot variability. Bromodomains represent potential affinity reagents for acetylated proteins and peptides, given their natural role in recognition of acetylated sequence motifs in vivo. To evaluate their efficacy, we generated recombinant proteins representing all known yeast bromodomains. Bromodomain specificity for acetylated peptides was determined using degenerate peptide arrays, leading to the observation that different bromodomains display a wide array of binding specificities. Despite their relatively weak affinity, we demonstrate the ability of selected bromodomains to enrich acetylated peptides from a complex biological mixture prior to mass spectrometric analysis. Finally, we demonstrate a method for improving the utility of bromodomain enrichment for MS through engineering novel affinity reagents using combinatorial tandem bromodomain pairs.

Computer aided manual validation of mass spectrometry-based proteomic data.

Advances in mass spectrometry-based proteomic technologies have increased the speed of analysis and the depth provided by a single analysis. Computational tools to evaluate the accuracy of peptide identifications from these high-throughput analyses have not kept pace with technological advances; currently the most common quality evaluation methods are based on statistical analysis of the likelihood of false positive identifications in large-scale data sets. While helpful, these calculations do not consider the accuracy of each identification, thus creating a precarious situation for biologists relying on the data to inform experimental design. Manual validation is the gold standard approach to confirm accuracy of database identifications, but is extremely time-intensive. To palliate the increasing time required to manually validate large proteomic datasets, we provide computer aided manual validation software (CAMV) to expedite the process. Relevant spectra are collected, catalogued, and pre-labeled, allowing users to efficiently judge the quality of each identification and summarize applicable quantitative information. CAMV significantly reduces the burden associated with manual validation and will hopefully encourage broader adoption of manual validation in mass spectrometry-based proteomics.

Molecular characterization of EGFR and EGFRvIII signaling networks in human glioblastoma tumor xenografts.

Glioblastoma multiforme (GBM) is a malignant primary brain tumor with a mean survival of 15 months with the current standard of care. Genetic profiling efforts have identified the amplification, overexpression, and mutation of the wild-type (wt) epidermal growth factor receptor tyrosine kinase (EGFR) in ≈ 50% of GBM patients. The genetic aberration of wtEGFR is frequently accompanied by the overexpression of a mutant EGFR known as EGFR variant III (EGFRvIII, de2-7EGFR, ΔEGFR), which is expressed in 30% of GBM tumors. The molecular mechanisms of tumorigenesis driven by EGFRvIII overexpression in human tumors have not been fully elucidated. To identify specific therapeutic targets for EGFRvIII driven tumors, it is important to gather a broad understanding of EGFRvIII specific signaling. Here, we have characterized signaling through the quantitative analysis of protein expression and tyrosine phosphorylation across a panel of glioblastoma tumor xenografts established from patient surgical specimens expressing wtEGFR or overexpressing wtEGFR (wtEGFR+) or EGFRvIII (EGFRvIII+). S100A10 (p11), major vault protein, guanylate-binding protein 1(GBP1), and carbonic anhydrase III (CAIII) were identified to have significantly increased expression in EGFRvIII expressing xenograft tumors relative to wtEGFR xenograft tumors. Increased expression of these four individual proteins was found to be correlated with poor survival in patients with GBM; the combination of these four proteins represents a prognostic signature for poor survival in gliomas. Integration of protein expression and phosphorylation data has uncovered significant heterogeneity among the various tumors and has highlighted several novel pathways, related to EGFR trafficking, activated in glioblastoma. The pathways and proteins identified in these tumor xenografts represent potential therapeutic targets for this disease.

Proximity labeling defines the phagosome lumen proteome of murine and primary human macrophages.

Proteomic analyses of the phagosome has significantly improved our understanding of the proteins which contribute to critical phagosome functions such as apoptotic cell clearance and microbial killing. However, previous methods of isolating phagosomes for proteomic analysis have relied on cell fractionation with some intrinsic limitations. Here, we present an alternative and modular proximity-labeling based strategy for mass spectrometry proteomic analysis of the phagosome lumen, termed PhagoID. We optimize proximity labeling in the phagosome and apply PhagoID to immortalized murine macrophages as well as primary human macrophages. Analysis of proteins detected by PhagoID in murine macrophages demonstrate that PhagoID corroborates previous proteomic studies, but also nominates novel proteins with unexpected residence at the phagosome for further study. A direct comparison between the proteins detected by PhagoID between mouse and human macrophages further reveals that human macrophage phagosomes have an increased abundance of proteins involved in the oxidative burst and antigen presentation. Our study develops and benchmarks a new approach to measure the protein composition of the phagosome and validates a subset of these findings, ultimately using PhagoID to grant further insight into the core constituent proteins and species differences at the phagosome lumen.

Scanorama: integrating large and diverse single-cell transcriptomic datasets.

Merging diverse single-cell RNA sequencing (scRNA-seq) data from numerous experiments, laboratories and technologies can uncover important biological insights. Nonetheless, integrating scRNA-seq data encounters special challenges when the datasets are composed of diverse cell type compositions. Scanorama offers a robust solution for improving the quality and interpretation of heterogeneous scRNA-seq data by effectively merging information from diverse sources. Scanorama is designed to address the technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of multiple scRNA-seq datasets. Here we provide a detailed protocol for using Scanorama within a Scanpy-based single-cell analysis workflow coupled with Google Colaboratory, a cloud-based free Jupyter notebook environment service. The protocol involves Scanorama integration, a process that typically spans 0.5-3 h. Scanorama integration requires a basic understanding of cellular biology, transcriptomic technologies and bioinformatics. Our protocol and new Scanorama-Colaboratory resource should make scRNA-seq integration more widely accessible to researchers.

PathMHC: a workflow to selectively target pathogen-derived MHC peptides in discovery immunopeptidomics experiments for vaccine target identification.

Vaccine-elicited T cell responses can contribute to immune protection against emerging infectious disease risks such as antimicrobials-resistant (AMR) microbial pathogens and viruses with pandemic potential, but rapidly identifying appropriate targets for T cell priming vaccines remains challenging. Mass spectrometry (MS) analysis of peptides presented on major histocompatibility complexes (MHCs) can identify potential targets for protective T cell responses in a proteome-wide manner. However, pathogen-derived peptides are outnumbered by self peptides in the MHC repertoire and may be missed in untargeted MS analyses. Here we present a novel approach, termed PathMHC, that uses computational analysis of untargeted MS data followed by targeted MS to discover novel pathogen-derived MHC peptides more efficiently than untargeted methods alone. We applied this workflow to identify MHC peptides derived from multiple microbes, including potential vaccine targets presented on MHC-I by human dendritic cells infected with Mycobacterium tuberculosis . PathMHC will facilitate antigen discovery campaigns for vaccine development.