Trimodal single-cell profiling reveals a novel pediatric CD8αα+ T cell subset and broad age-related molecular reprogramming across the T cell compartment.

Age-associated changes in the T cell compartment are well described. However, limitations of current single-modal or bimodal single-cell assays, including flow cytometry, RNA-seq (RNA sequencing) and CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), have restricted our ability to deconvolve more complex cellular and molecular changes. Here, we profile >300,000 single T cells from healthy children (aged 11-13 years) and older adults (aged 55-65 years) by using the trimodal assay TEA-seq (single-cell analysis of mRNA transcripts, surface protein epitopes and chromatin accessibility), which revealed that molecular programming of T cell subsets shifts toward a more activated basal state with age. Naive CD4+ T cells, considered relatively resistant to aging, exhibited pronounced transcriptional and epigenetic reprogramming. Moreover, we discovered a novel CD8αα+ T cell subset lost with age that is epigenetically poised for rapid effector responses and has distinct inhibitory, costimulatory and tissue-homing properties. Together, these data reveal new insights into age-associated changes in the T cell compartment that may contribute to differential immune responses.

Persistent serum protein signatures define an inflammatory subcategory of long COVID.

Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months following acute SARS-CoV-2 infection. The aetiologies may include persistent inflammation, unresolved tissue damage or delayed clearance of viral protein or RNA, but the biological differences they represent are not fully understood. Here we evaluate the serum proteome in samples, longitudinally collected from 55 PASC individuals with symptoms lasting ≥60 days after onset of acute infection, in comparison to samples from symptomatically recovered SARS-CoV-2 infected and uninfected individuals. Our analysis indicates heterogeneity in PASC and identified subsets with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-κB signaling (particularly associated with TNF), appear to be the most differentially enriched signaling pathways, distinguishing a group of patients characterized also by a persistent neutrophil activation signature. These findings help to clarify biological diversity within PASC, identify participants with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance, including a protein panel that we propose as having diagnostic utility for differentiating inflammatory and non-inflammatory PASC.

A comprehensive platform for analyzing longitudinal multi-omics data.

Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO ( https://github.com/aifimmunology/PALMO ), a platform that contains five analytical modules to examine longitudinal bulk and single-cell multi-omics data from multiple perspectives, including decomposition of sources of variations within the data, collection of stable or variable features across timepoints and participants, identification of up- or down-regulated markers across timepoints of individual participants, and investigation on samples of same participants for possible outlier events. We have tested PALMO performance on a complex longitudinal multi-omics dataset of five data modalities on the same samples and six external datasets of diverse background. Both PALMO and our longitudinal multi-omics dataset can be valuable resources to the scientific community.

A proteogenomic portrait of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Longitudinal immune dynamics of mild COVID-19 define signatures of recovery and persistence.

SARS-CoV-2 has infected over 200 million and caused more than 4 million deaths to date. Most individuals (>80%) have mild symptoms and recover in the outpatient setting, but detailed studies of immune responses have focused primarily on moderate to severe COVID-19. We deeply profiled the longitudinal immune response in individuals with mild COVID-19 beginning with early time points post-infection (1-15 days) and proceeding through convalescence to >100 days after symptom onset. We correlated data from single cell analyses of peripheral blood cells, serum proteomics, virus-specific cellular and humoral immune responses, and clinical metadata. Acute infection was characterized by vigorous coordinated innate and adaptive immune activation that differed in character by age (young vs. old). We then characterized signals associated with recovery and convalescence to define and validate a new signature of inflammatory cytokines, gene expression, and chromatin accessibility that persists in individuals with post-acute sequelae of SARS-CoV-2 infection (PASC).

Identification of EMT signaling cross-talk and gene regulatory networks by single-cell RNA sequencing.

The epithelial-to-mesenchymal transition (EMT) plays a critical role during normal development and in cancer progression. EMT is induced by various signaling pathways, including TGF-ß, BMP, Wnt-ß-catenin, NOTCH, Shh, and receptor tyrosine kinases. In this study, we performed single-cell RNA sequencing on MCF10A cells undergoing EMT by TGF-ß1 stimulation. Our comprehensive analysis revealed that cells progress through EMT at different paces. Using pseudotime clustering reconstruction of gene-expression profiles during EMT, we found sequential and parallel activation of EMT signaling pathways. We also observed various transitional cellular states during EMT. We identified regulatory signaling nodes that drive EMT with the expression of important microRNAs and transcription factors. Using a random circuit perturbation methodology, we demonstrate that the NOTCH signaling pathway acts as a key driver of TGF-ß-induced EMT. Furthermore, we demonstrate that the gene signatures of pseudotime clusters corresponding to the intermediate hybrid EMT state are associated with poor patient outcome. Overall, this study provides insight into context-specific drivers of cancer progression and highlights the complexities of the EMT process.

EMTome: a resource for pan-cancer analysis of epithelial-mesenchymal transition genes and signatures.

BACKGROUND: The epithelial-mesenchymal transition (EMT) enables dissociation of tumour cells from the primary tumour mass, invasion through the extracellular matrix, intravasation into blood vessels and colonisation of distant organs. Cells that revert to the epithelial state via the mesenchymal-epithelial transition cause metastases, the primary cause of death in cancer patients. EMT also empowers cancer cells with stem-cell properties and induces resistance to chemotherapeutic drugs. Understanding the driving factors of EMT is critical for the development of effective therapeutic interventions. METHODS: This manuscript describes the generation of a database containing EMT gene signatures derived from cell lines, patient-derived xenografts and patient studies across cancer types and multiomics data and the creation of a web-based portal to provide a comprehensive analysis resource. RESULTS: EMTome incorporates (i) EMT gene signatures; (ii) EMT-related genes with multiomics features across different cancer types; (iii) interactomes of EMT-related genes (miRNAs, transcription factors, and proteins); (iv) immune profiles identified from The Cancer Genome Atlas (TCGA) cohorts by exploring transcriptomics, epigenomics, and proteomics, and drug sensitivity and (iv) clinical outcomes of cancer cohorts linked to EMT gene signatures. CONCLUSION: The web-based EMTome portal is a resource for primary and metastatic tumour research publicly available at www.emtome.org .

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Microscaled proteogenomic methods for precision oncology.

Cancer proteogenomics promises new insights into cancer biology and treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifications by mass spectrometry (MS). A critical limitation is sample input requirements that exceed many sources of clinically important material. Here we report a proteogenomics approach for core biopsies using tissue-sparing specimen processing and microscaled proteomics. As a demonstration, we analyze core needle biopsies from ERBB2 positive breast cancers before and 48-72 h after initiating neoadjuvant trastuzumab-based chemotherapy. We show greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identify potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression and an inactive immune microenvironment. The clinical utility and discovery potential of proteogenomics at biopsy-scale warrants further investigation.

LinkedOmics: analyzing multi-omics data within and across 32 cancer types.

The LinkedOmics database contains multi-omics data and clinical data for 32 cancer types and a total of 11 158 patients from The Cancer Genome Atlas (TCGA) project. It is also the first multi-omics database that integrates mass spectrometry (MS)-based global proteomics data generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) on selected TCGA tumor samples. In total, LinkedOmics has more than a billion data points. To allow comprehensive analysis of these data, we developed three analysis modules in the LinkedOmics web application. The LinkFinder module allows flexible exploration of associations between a molecular or clinical attribute of interest and all other attributes, providing the opportunity to analyze and visualize associations between billions of attribute pairs for each cancer cohort. The LinkCompare module enables easy comparison of the associations identified by LinkFinder, which is particularly useful in multi-omics and pan-cancer analyses. The LinkInterpreter module transforms identified associations into biological understanding through pathway and network analysis. Using five case studies, we demonstrate that LinkedOmics provides a unique platform for biologists and clinicians to access, analyze and compare cancer multi-omics data within and across tumor types. LinkedOmics is freely available at http://www.linkedomics.org.

HSP70 mediates survival in apoptotic cells-Boolean network prediction and experimental validation.

Neuronal stress or injury results in the activation of proteins, which regulate the balance between survival and apoptosis. However, the complex mechanism of cell signaling involving cell death and survival, activated in response to cellular stress is not yet completely understood. To bring more clarity about these mechanisms, a Boolean network was constructed that represented the apoptotic pathway in neuronal cells. FasL and neurotrophic growth factor (NGF) were considered as inputs in the absence and presence of heat shock proteins known to shift the balance toward survival by rescuing pro-apoptotic cells. The probabilities of survival, DNA repair and apoptosis as cellular fates, in the presence of either the growth factor or FasL, revealed a survival bias encoded in the network. Boolean predictions tested by measuring the mRNA level of caspase-3, caspase-8, and BAX in neuronal Neuro2a (N2a) cell line with NGF and FasL as external input, showed positive correlation with the observed experimental results for survival and apoptotic states. It was observed that HSP70 contributed more toward rescuing cells from apoptosis in comparison to HSP27, HSP40, and HSP90. Overexpression of HSP70 in N2a transfected cells showed reversal of cellular fate from FasL-induced apoptosis to survival. Further, the pro-survival role of the proteins BCL2, IAP, cFLIP, and NFκB determined by vertex perturbation analysis was experimentally validated through protein inhibition experiments using EM20-25, Embelin and Wedelolactone, which resulted in 1.27-, 1.26-, and 1.46-fold increase in apoptosis of N2a cells. The existence of a one-to-one correspondence between cellular fates and attractor states shows that Boolean networks may be employed with confidence in qualitative analytical studies of biological networks.

Selective interception of gelsolin amyloidogenic stretch results in conformationally distinct aggregates with reduced toxicity.

The pathogenesis of protein misfolding diseases is attributed to the cytotoxicity caused by amyloidogenic prefibrillar aggregates, rather than mature fibrils. The presence of one or more amyloidogenic stretches in different proteins has been proven critical for initiating fibril formation. In the present study, we show that two natural compounds, curcumin and emetine, bind tightly (Kd < 1.6 µM) to the core amyloidogenic stretch (182-192) of gelsolin (AGel). Binding happens in different structural orientations, distinctly modulating the amyloidogenic pathway of AGel. While AGel alone undergoes sigmoidal transition to thioflavin T (ThT)-responsive fibrillar aggregates with clear lag phase, the presence of curcumin or emetine abolishes the lag phase and produces starkly different, noncytotoxic end products. Atomic force microscopy revealed that while curcumin augments fibril formation, emetine arrests it at an intermediate aggregated stage with no fibrillar morphology. FTIR spectroscopy, dynamic light scattering, and ANS fluorescence experiments also suggest that these two species are distinct. Curcumin and emetine also differentially affect the preformed amyloids with the former thickening the fibrils and the latter releasing reclusive oligomers. MD simulations further provided mechanistic insights of differential interaction by the two compounds modulating amyloid formation. The results were also confirmed on the disease-associated amyloidogenic fragment of gelsolin (fAGel). Thus, our findings suggest that targeting amyloidogenic stretches in proteins could be useful in designing novel molecules against protein misfolding diseases.

Modulation of neuronal proteome profile in response to Japanese encephalitis virus infection.

In this study we have reported the in vivo proteomic changes during Japanese Encephalitis Virus (JEV) infection in combination with in vitro studies which will help in the comprehensive characterization of the modifications in the host metabolism in response to JEV infection. We performed a 2-DE based quantitative proteomic study of JEV-infected mouse brain as well as mouse neuroblastoma (Neuro2a) cells to analyze the host response to this lethal virus. 56 host proteins were found to be differentially expressed post JEV infection (defined as exhibiting ≥ 1.5-fold change in protein abundance upon JEV infection). Bioinformatics analyses were used to generate JEV-regulated host response networks which reported that the identified proteins were found to be associated with various cellular processes ranging from intracellular protein transport, cellular metabolism and ER stress associated unfolded protein response. JEV was found to invade the host protein folding machinery to sustain its survival and replication inside the host thereby generating a vigorous unfolded protein response, subsequently triggering a number of pathways responsible for the JEV associated pathologies. The results were also validated using a human cell line to correlate them to the human response to JEV. The present investigation is the first report on JEV-host interactome in in vivo model and will be of potential interest for future antiviral research in this field.

Fast prediction of deleterious angiogenin mutations causing amyotrophic lateral sclerosis.

Certain single nucleotide polymorphisms causing missense mutations in angiogenin result in its loss-of-function and onset of amyotrophic lateral sclerosis (ALS). Although several such associations are reported across diverse ethnic groups, no method is available for predicting if a new mutation is deleterious. We present here a fast molecular dynamics based method for determining the mechanisms of functional loss caused by mutations, and attributes to ascertain whether a mutation causes ALS.

NeuroDNet - an open source platform for constructing and analyzing neurodegenerative disease networks.

BACKGROUND: Genetic networks control cellular functions. Aberrations in normal cellular function are caused by mutations in genes that disrupt the fine tuning of genetic networks and cause disease or disorder. However, the large number of signalling molecules, genes and proteins that constitute such networks, and the consequent complexity of interactions, has restrained progress in research elucidating disease mechanisms. Hence, carrying out a systematic analysis of how diseases alter the character of these networks is important. We illustrate this through our work on neurodegenerative disease networks. We created a database, NeuroDNet, which brings together relevant information about signalling molecules, genes and proteins, and their interactions, for constructing neurodegenerative disease networks. DESCRIPTION: NeuroDNet is a database with interactive tools that enables the creation of interaction networks for twelve neurodegenerative diseases under one portal for interrogation and analyses. It is the first of its kind, which enables the construction and analysis of neurodegenerative diseases through protein interaction networks, regulatory networks and Boolean networks. The database has a three-tier architecture - foundation, function and interface. The foundation tier contains the human genome data with 23857 protein-coding genes linked to more than 300 genes reported in clinical studies of neurodegenerative diseases. The database architecture was designed to retrieve neurodegenerative disease information seamlessly through the interface tier using specific functional information. Features of this database enable users to extract, analyze and display information related to a disease in many different ways. CONCLUSIONS: The application of NeuroDNet was illustrated using three case studies. Through these case studies, the construction and analyses of a PPI network for angiogenin protein in amyotrophic lateral sclerosis, a signal-gene-protein interaction network for presenilin protein in Alzheimer's disease and a Boolean network for a mammalian cell cycle was demonstrated. NeuroDNet is accessible at http://bioschool.iitd.ac.in/NeuroDNet/.

ANGDelMut - a web-based tool for predicting and analyzing functional loss mechanisms of amyotrophic lateral sclerosis-associated angiogenin mutations.

ANGDelMut is a web-based tool for predicting the functional consequences of missense mutations in the angiogenin (ANG) protein, which is associated with amyotrophic lateral sclerosis (ALS). Missense mutations in ANG result in loss of either ribonucleolytic activity or nuclear translocation activity or both of these functions, and in turn cause ALS. However, no web-based tools are available to predict whether a newly identified ANG mutation will possibly lead to ALS. More importantly, no web-implemented method is currently available to predict the mechanisms of loss-of-function(s) of ANG mutants. In light of this observation, we developed the ANGDelMut web-based tool, which predicts whether an ANG mutation is deleterious or benign. The user selects certain attributes from the input panel, which serves as a query to infer whether a mutant will exhibit loss of ribonucleolytic activity or nuclear translocation activity or whether the overall stability will be affected. The output states whether the mutation is deleterious or benign, and if it is deleterious, gives the possible mechanism(s) of loss-of-function. This web-based tool, freely available at http://bioschool.iitd.ernet.in/DelMut/, is the first of its kind to provide a platform for researchers and clinicians, to infer the functional consequences of ANG mutations and correlate their possible association with ALS ahead of experimental findings.

Mechanisms of loss of functions of human angiogenin variants implicated in amyotrophic lateral sclerosis.

BACKGROUND: Mutations in the coding region of angiogenin (ANG) gene have been found in patients suffering from Amyotrophic Lateral Sclerosis (ALS). Neurodegeneration results from the loss of angiogenic ability of ANG (protein coded by ANG). In this work, we performed extensive molecular dynamics (MD) simulations of wild-type ANG and disease associated ANG variants to elucidate the mechanism behind the loss of ribonucleolytic activity and nuclear translocation activity, functions needed for angiogenesis. METHODOLOGY/PRINCIPAL FINDINGS: MD simulations were carried out to study the structural and dynamic differences in the catalytic site and nuclear localization signal residues between WT-ANG (Wild-type ANG) and six mutants. Variants K17I, S28N, P112L and V113I have confirmed association with ALS, while T195C and A238G single nucleotide polymorphisms (SNPs) encoding L35P and K60E mutants respectively, have not been associated with ALS. Our results show that loss of ribonucleolytic activity in K17I is caused by conformational switching of the catalytic residue His114 by 99°. The loss of nuclear translocation activity of S28N and P112L is caused by changes in the folding of the residues (31)RRR(33) that result in the reduction in solvent accessible surface area (SASA). Consequently, we predict that V113I will exhibit loss of angiogenic properties by loss of nuclear translocation activity and L35P by loss of both ribonucleolytic activity and nuclear translocation activity. No functional loss was inferred for K60E. The MD simulation results were supported by hydrogen bond interaction analyses and molecular docking studies. CONCLUSIONS/SIGNIFICANCE: Conformational switching of catalytic residue His114 seems to be the mechanism causing loss of ribonucleolytic activity and reduction in SASA of nuclear localization signal residues (31)RRR(33) results in loss of nuclear translocation activity in ANG mutants. Therefore, we predict that L35P mutant, would exhibit loss of angiogenic functions, and hence would correlate with ALS while K60E would not show any loss.