Defining and targeting tumor-associated macrophages in malignant mesothelioma.

Defining the ontogeny of tumor-associated macrophages (TAM) is important to develop therapeutic targets for mesothelioma. We identified two distinct macrophage populations in mouse peritoneal and pleural cavities, the monocyte-derived, small peritoneal/pleural macrophages (SPM), and the tissue-resident large peritoneal/pleural macrophages (LPM). SPM rapidly increased in tumor microenvironment after tumor challenge and contributed to the vast majority of M2-like TAM. The selective depletion of M2-like TAM by conditional deletion of the Dicer1 gene in myeloid cells (D-/-) promoted tumor rejection. Sorted SPM M2-like TAM initiated tumorigenesis in vivo and in vitro, confirming their capacity to support tumor development. The transcriptomic and single-cell RNA sequencing analysis demonstrated that both SPM and LPM contributed to the tumor microenvironment by promoting the IL-2-STAT5 signaling pathway, inflammation, and epithelial-mesenchymal transition. However, while SPM preferentially activated the KRAS and TNF-α/NFkB signaling pathways, LPM activated the IFN-γ response. The importance of LPM in the immune response was confirmed by depleting LPM with intrapleural clodronate liposomes, which abrogated the antitumoral memory immunity. SPM gene signature could be identified in pleural effusion and tumor from patients with untreated mesothelioma. Five genes, TREM2, STAB1, LAIR1, GPNMB, and MARCO, could potentially be specific therapeutic targets. Accordingly, Trem2 gene deletion led to reduced SPM M2-like TAM with compensatory increase in LPM and slower tumor growth. Overall, these experiments demonstrate that SPM M2-like TAM play a key role in mesothelioma development, while LPM more specifically contribute to the immune response. Therefore, selective targeting of monocyte-derived TAM may enhance antitumor immunity through compensatory expansion of tissue-resident TAM.

Transcriptome Analysis Identifies Oncogenic Tissue Remodeling during Progression from Common Nevi to Early Melanoma.

Early detection and treatment of melanoma, the most aggressive skin cancer, improves the median 5-year survival rate of patients from 25% to 99%. Melanoma development involves a stepwise process during which genetic changes drive histologic alterations within nevi and surrounding tissue. Herein, a comprehensive analysis of publicly available gene expression data sets of melanoma, common or congenital nevi (CN), and dysplastic nevi (DN), assessed molecular and genetic pathways leading to early melanoma. The results demonstrate several pathways reflective of ongoing local structural tissue remodeling activity likely involved during the transition from benign to early-stage melanoma. These processes include the gene expression of cancer-associated fibroblasts, collagens, extracellular matrix, and integrins, which assist early melanoma development and the immune surveillance that plays a substantial role at this early stage. Furthermore, genes up-regulated in DN were also overexpressed in melanoma tissue, supporting the notion that DN may serve as a transitional phase toward oncogenesis. CN collected from healthy individuals exhibited different gene signatures compared with histologically benign nevi tissue located adjacent to melanoma (adjacent nevi). Finally, the expression profile of microdissected adjacent nevi tissue was more similar to melanoma compared with CN, revealing the melanoma influence on this annexed tissue.

Myeloablative autologous haematopoietic stem cell transplantation resets the B cell repertoire to a more naïve state in patients with systemic sclerosis.

OBJECTIVES: Myeloablative autologous haematopoietic stem cell transplant (HSCT) was recently demonstrated to provide significant benefit over cyclophosphamide (CYC) in the treatment of diffuse cutaneous systemic sclerosis (dcSSc) in the Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial. As dysregulation of the B cell compartment has previously been described in dcSSc, we sought to gain insight into the effects of myeloablative autologous HSCT as compared with CYC. METHODS: We sequenced the peripheral blood immunoglobulin heavy chain (IGH) repertoires in patients with dcSSc enrolled in the SCOT trial. RESULTS: Myeloablative autologous HSCT was associated with a sustained increase in IgM isotype antibodies bearing a low mutation rate. Clonal expression was reduced in IGH repertoires following myeloablative autologous HSCT. Additionally, we identified a underusage of immunoglobulin heavy chain V gene 5-51 in patients with dcSSc, and usage normalised following myeloablative autologous HSCT but not CYC treatment. CONCLUSIONS: Together, these findings suggest that myeloablative autologous HSCT resets the IGH repertoire to a more naïve state characterised by IgM-expressing B cells, providing a possible mechanism for the elimination of pathogenic B cells that may contribute to the benefit of HSCT over CYC in the treatment of dcSSc.

SARS-CoV-2-Reactive Mucosal B Cells in the Upper Respiratory Tract of Uninfected Individuals.

SARS-CoV-2 is a respiratory pathogen that can cause severe disease in at-risk populations but results in asymptomatic infections or a mild course of disease in the majority of cases. We report the identification of SARS-CoV-2-reactive B cells in human tonsillar tissue obtained from children who were negative for coronavirus disease 2019 prior to the pandemic and the generation of mAbs recognizing the SARS-CoV-2 Spike protein from these B cells. These Abs showed reduced binding to Spike proteins of SARS-CoV-2 variants and did not recognize Spike proteins of endemic coronaviruses, but subsets reacted with commensal microbiota and exhibited SARS-CoV-2-neutralizing potential. Our study demonstrates pre-existing SARS-CoV-2-reactive Abs in various B cell populations in the upper respiratory tract lymphoid tissue that may lead to the rapid engagement of the pathogen and contribute to prevent manifestations of symptomatic or severe disease.

Candidate variants in TUB are associated with familial tremor.

Essential tremor (ET) is the most common adult-onset movement disorder. In the present study, we performed whole exome sequencing of a large ET-affected family (10 affected and 6 un-affected family members) and identified a TUB p.V431I variant (rs75594955) segregating in a manner consistent with autosomal-dominant inheritance. Subsequent targeted re-sequencing of TUB in 820 unrelated individuals with sporadic ET and 630 controls revealed significant enrichment of rare nonsynonymous TUB variants (e.g. rs75594955: p.V431I, rs1241709665: p.Ile20Phe, rs55648406: p.Arg49Gln) in the ET cohort (SKAT-O test p-value = 6.20e-08). TUB encodes a transcription factor predominantly expressed in neuronal cells and has been previously implicated in obesity. ChIP-seq analyses of the TUB transcription factor across different regions of the mouse brain revealed that TUB regulates the pathways responsible for neurotransmitter production as well thyroid hormone signaling. Together, these results support the association of rare variants in TUB with ET.

Prognostic Value of EMT Gene Signature in Malignant Mesothelioma.

Malignant mesothelioma (MESO) consists of epithelioid, biphasic, and sarcomatoid subtypes with different epithelial-mesenchymal transition (EMT) phenotypes. We previously identified a panel of four MESO EMT genes correlating with an immunosuppressive tumor microenvironment and poor survival. In this study, we investigated the correlation between these MESO EMT genes, the immune profile, and the genomic and epigenomic alterations to identify potential therapeutic targets to prevent or reverse the EMT process. Using multiomic analysis, we observed that the MESO EMT genes were positively correlated with hypermethylation of epigenetic genes and loss of CDKN2A/B expression. MESO EMT genes such as COL5A2, ITGAV, SERPINH1, CALD1, SPARC, and ACTA2 were associated with upregulation of TGF-ß signaling, hedgehog signaling, and IL-2-STAT5 signaling and downregulation of the IFN-α and IFN-γ response. Immune checkpoints such as CTLA4, CD274 (PD-L1), PDCD1LG2 (PD-L2), PDCD1 (PD-1), and TIGIT were upregulated, while LAG3, LGALS9, and VTCN1 were downregulated with the expression of MESO EMT genes. CD160, KIR2DL1, and KIR2DL3 were also broadly downregulated with the expression of MESO EMT genes. In conclusion, we observed that the expression of a panel of MESO EMT genes was associated with hypermethylation of epigenetic genes and loss of expression of CDKN2A and CDKN2B. Expression of MESO EMT genes was associated with downregulation of the type I and type II IFN response, loss of cytotoxicity and NK cell activity, and upregulation of specific immune checkpoints, as well as upregulation of the TGF-ß1/TGFBR1 pathway.

Convergent CDR3 homology amongst Spike-specific antibody responses in convalescent COVID-19 subjects receiving the BNT162b2 vaccine.

Convalescent coronavirus disease 2019 (COVID-19) subjects who receive BNT162b2 develop robust antibody responses against SARS-CoV-2. However, our understanding of the clonal B cell response pre- and post-vaccination in such individuals is limited. Here we characterized B cell phenotypes and the BCR repertoire after BNT162b2 immunization in two convalescent COVID-19 subjects. BNT162b2 stimulated many B cell clones that were under-represented during SARS-CoV-2 infection. In addition, the vaccine generated B cell clusters with >65% similarity in CDR3 VH and VL region consensus sequences both within and between subjects. This result suggests that the CDR3 region plays a dominant role adjacent to heavy and light chain V/J pairing in the recognition of the SARS-CoV-2 spike protein. Antigen-specific B cell populations with homology to published SARS-CoV-2 antibody sequences from the CoV-AbDab database were observed in both subjects. These results point towards the development of convergent antibody responses against the virus in different individuals.

RNA-seq characterization of histamine-releasing mast cells as potential therapeutic target of osteoarthritis.

OBJECTIVE: Mast cells in the osteoarthritis (OA) synovium correlate with disease severity. This study aimed to further elucidate the role of mast cells in OA by RNA-Seq analysis and pharmacological blockade of the activity of histamine, a key mast cell mediator, in murine OA. METHODS: We examined OA synovial tissues and fluids by flow cytometry, immunostaining, single-cell and bulk RNA-Seq, qPCR, and ELISA. Cetirizine, a histamine H1 receptor (H1R) antagonist, was used to treat the destabilization of the medial meniscus (DMM) mouse model of OA. RESULTS: Flow cytometry and immunohistology analysis of OA synovial cells revealed KIT+ FcεRI+ and TPSAB1+ mast cells. Single-cell RNA-Seq of OA synovial cells identified the expression of prototypical mast cell markers KIT, TPSAB1, CPA3 and HDC, as well as distinctive markers HPGD, CAVIN2, IL1RL1, PRG2, and CKLF, confirmed by bulk RNA-Seq and qPCR. A mast cell prototypical marker expression score classified 40 OA patients into three synovial pathotypes: mast cell-high, -medium, and -low. Additionally, we detected mast cell mediators including histamine, tryptase AB1, CPA3, PRG2, CAVIN2, and CKLF in OA synovial fluids. Elevated H1R expression was detected in human OA synovium, and treatment of mice with the H1 receptor antagonist cetirizine reduced the severity and OA-related mediators in DMM. CONCLUSION: Based on differential expression of prototypical and distinct mast cell markers, human OA joints can be stratified into mast cell-high, -medium, and -low synovial tissue pathotypes. Pharmacologic blockade of histamine activity holds the potential to improve OA disease outcome.

BPG: Seamless, automated and interactive visualization of scientific data.

BACKGROUND: We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. RESULTS: This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. CONCLUSION: BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Association of AHSG with alopecia and mental retardation (APMR) syndrome.

Alopecia with mental retardation syndrome (APMR) is a very rare autosomal recessive condition that is associated with total or partial absence of hair from the scalp and other parts of the body as well as variable intellectual disability. Here we present whole-exome sequencing results of a large consanguineous family segregating APMR syndrome with seven affected family members. Our study revealed a novel predicted pathogenic, homozygous missense mutation in the AHSG (OMIM 138680) gene (AHSG: NM_001622:exon7:c.950G>A:p.Arg317His). The variant is predicted to affect a region of the protein required for protein processing and disrupts a phosphorylation motif. In addition, the altered protein migrates with an aberrant size relative to healthy individuals. Consistent with the phenotype, AHSG maps within APMR linkage region 1 (APMR 1) as reported before, and falls within runs of homozygosity (ROH). Previous families with APMR syndrome have been studied through linkage analyses and the linkage resolution did not allow pointing out to a single gene candidate. Our study is the first report to identify a homozygous missense mutation for APMR syndrome through whole-exome sequencing.

A high-definition view of functional genetic variation from natural yeast genomes.

The question of how genetic variation in a population influences phenotypic variation and evolution is of major importance in modern biology. Yet much is still unknown about the relative functional importance of different forms of genome variation and how they are shaped by evolutionary processes. Here we address these questions by population level sequencing of 42 strains from the budding yeast Saccharomyces cerevisiae and its closest relative S. paradoxus. We find that genome content variation, in the form of presence or absence as well as copy number of genetic material, is higher within S. cerevisiae than within S. paradoxus, despite genetic distances as measured in single-nucleotide polymorphisms being vastly smaller within the former species. This genome content variation, as well as loss-of-function variation in the form of premature stop codons and frameshifting indels, is heavily enriched in the subtelomeres, strongly reinforcing the relevance of these regions to functional evolution. Genes affected by these likely functional forms of variation are enriched for functions mediating interaction with the external environment (sugar transport and metabolism, flocculation, metal transport, and metabolism). Our results and analyses provide a comprehensive view of genomic diversity in budding yeast and expose surprising and pronounced differences between the variation within S. cerevisiae and that within S. paradoxus. We also believe that the sequence data and de novo assemblies will constitute a useful resource for further evolutionary and population genomics studies.

ShatterProof: operational detection and quantification of chromothripsis.

BACKGROUND: Chromothripsis, a newly discovered type of complex genomic rearrangement, has been implicated in the evolution of several types of cancers. To date, it has been described in bone cancer, SHH-medulloblastoma and acute myeloid leukemia, amongst others, however there are still no formal or automated methods for detecting or annotating it in high throughput sequencing data. As such, findings of chromothripsis are difficult to compare and many cases likely escape detection altogether. RESULTS: We introduce ShatterProof, a software tool for detecting and quantifying chromothriptic events. ShatterProof takes structural variation calls (translocations, copy-number variations, short insertions and loss of heterozygosity) produced by any algorithm and using an operational definition of chromothripsis performs robust statistical tests to accurately predict the presence and location of chromothriptic events. Validation of our tool was conducted using clinical data sets including matched normal, prostate cancer samples in addition to the colorectal cancer and SCLC data sets used in the original description of chromothripsis. CONCLUSIONS: ShatterProof is computationally efficient, having low memory requirements and near linear computation time. This allows it to become a standard component of sequencing analysis pipelines, enabling researchers to routinely and accurately assess samples for chromothripsis. Source code and documentation can be found at http://search.cpan.org/~sgovind/Shatterproof.

Revealing the genetic structure of a trait by sequencing a population under selection.

One approach to understanding the genetic basis of traits is to study their pattern of inheritance among offspring of phenotypically different parents. Previously, such analysis has been limited by low mapping resolution, high labor costs, and large sample size requirements for detecting modest effects. Here, we present a novel approach to map trait loci using artificial selection. First, we generated populations of 10-100 million haploid and diploid segregants by crossing two budding yeast strains of different heat tolerance for up to 12 generations. We then subjected these large segregant pools to heat stress for up to 12 d, enriching for beneficial alleles. Finally, we sequenced total DNA from the pools before and during selection to measure the changes in parental allele frequency. We mapped 21 intervals with significant changes in genetic background in response to selection, which is several times more than found with traditional linkage methods. Nine of these regions contained two or fewer genes, yielding much higher resolution than previous genomic linkage studies. Multiple members of the RAS/cAMP signaling pathway were implicated, along with genes previously not annotated with heat stress response function. Surprisingly, at most selected loci, allele frequencies stopped changing before the end of the selection experiment, but alleles did not become fixed. Furthermore, we were able to detect the same set of trait loci in a population of diploid individuals with similar power and resolution, and observed primarily additive effects, similar to what is seen for complex trait genetics in other diploid organisms such as humans.

Trait variation in yeast is defined by population history.

A fundamental goal in biology is to achieve a mechanistic understanding of how and to what extent ecological variation imposes selection for distinct traits and favors the fixation of specific genetic variants. Key to such an understanding is the detailed mapping of the natural genomic and phenomic space and a bridging of the gap that separates these worlds. Here we chart a high-resolution map of natural trait variation in one of the most important genetic model organisms, the budding yeast Saccharomyces cerevisiae, and its closest wild relatives and trace the genetic basis and timing of major phenotype changing events in its recent history. We show that natural trait variation in S. cerevisiae exceeds that of its relatives, despite limited genetic variation, and follows the population history rather than the source environment. In particular, the West African population is phenotypically unique, with an extreme abundance of low-performance alleles, notably a premature translational termination signal in GAL3 that cause inability to utilize galactose. Our observations suggest that many S. cerevisiae traits may be the consequence of genetic drift rather than selection, in line with the assumption that natural yeast lineages are remnants of recent population bottlenecks. Disconcertingly, the universal type strain S288C was found to be highly atypical, highlighting the danger of extrapolating gene-trait connections obtained in mosaic, lab-domesticated lineages to the species as a whole. Overall, this study represents a step towards an in-depth understanding of the causal relationship between co-variation in ecology, selection pressure, natural traits, molecular mechanism, and alleles in a key model organism.

High throughput long-read sequencing of circulating lymphocytes of the evolutionarily distant sea lamprey reveals diversity and common elements of the variable lymphocyte receptor B (VLRB) repertoire.

The leucine-rich repeat-based variable lymphocyte receptor B (VLRB) antibody system of jawless vertebrates is capable of generating an antibody repertoire equal to or exceeding the diversity of antibody repertoires of jawed vertebrates. Unlike immunoglobulin-based immune repertoires, the VLRB repertoire diversity is characterized by variable lengths of VLRB encoding transcripts, rendering conventional immunoreceptor repertoire sequencing approaches unsuitable for VLRB repertoire sequencing. Here we demonstrate that long-read single-molecule real-time (SMRT) sequencing (PacBio) approaches permit the efficient large-scale assessment of the VLRB repertoire. We present a computational pipeline for sequence data processing and provide the first repertoire-based analysis of VLRB protein characteristics including properties of its subunits and regions of diversity within each structural leucine-rich repeat subunit. Our study provides a template to explore changes in the VLRB repertoire during immune responses and to establish large scale VLRB repertoire databases for computational approaches aimed at isolating monoclonal VLRB reagents for biomedical research and clinical applications.

Multifaceted immune dysregulation characterizes individuals at-risk for rheumatoid arthritis.

Molecular markers of autoimmunity, such as antibodies to citrullinated protein antigens (ACPA), are detectable prior to inflammatory arthritis (IA) in rheumatoid arthritis (RA) and may define a state that is 'at-risk' for future RA. Here we present a cross-sectional comparative analysis among three groups that include ACPA positive individuals without IA (At-Risk), ACPA negative individuals and individuals with early, ACPA positive clinical RA (Early RA). Differential methylation analysis among the groups identifies non-specific dysregulation in peripheral B, memory and naïve T cells in At-Risk participants, with more specific immunological pathway abnormalities in Early RA. Tetramer studies show increased abundance of T cells recognizing citrullinated (cit) epitopes in At-Risk participants, including expansion of T cells reactive to citrullinated cartilage intermediate layer protein I (cit-CILP); these T cells have Th1, Th17, and T stem cell memory-like phenotypes. Antibody-antigen array analyses show that antibodies targeting cit-clusterin, cit-fibrinogen and cit-histone H4 are elevated in At-Risk and Early RA participants, with the highest levels of antibodies detected in those with Early RA. These findings indicate that an ACPA positive at-risk state is associated with multifaceted immune dysregulation that may represent a potential opportunity for targeted intervention.

Towards a theoretical understanding of false positives in DNA motif finding.

BACKGROUND: Detection of false-positive motifs is one of the main causes of low performance in de novo DNA motif-finding methods. Despite the substantial algorithm development effort in this area, recent comprehensive benchmark studies revealed that the performance of DNA motif-finders leaves room for improvement in realistic scenarios. RESULTS: Using large-deviations theory, we derive a remarkably simple relationship that describes the dependence of false positives on dataset size for the one-occurrence per sequence motif-finding problem. As expected, we predict that false-positives can be reduced by decreasing the sequence length or by adding more sequences to the dataset. Interestingly, we find that the false-positive strength depends more strongly on the number of sequences in the dataset than it does on the sequence length, but that the dependence on the number of sequences diminishes, after which adding more sequences does not reduce the false-positive rate significantly. We compare our theoretical predictions by applying four popular motif-finding algorithms that solve the one-occurrence-per-sequence problem (MEME, the Gibbs Sampler, Weeder, and GIMSAN) to simulated data that contain no motifs. We find that the dependence of false positives detected by these softwares on the motif-finding parameters is similar to that predicted by our formula. CONCLUSIONS: We quantify the relationship between the sequence search space and motif-finding false-positives. Based on the simple formula we derive, we provide a number of intuitive rules of thumb that may be used to enhance motif-finding results in practice. Our results provide a theoretical advance in an important problem in computational biology.

Ranking insertion, deletion and nonsense mutations based on their effect on genetic information.

BACKGROUND: Genetic variations contribute to normal phenotypic differences as well as diseases, and new sequencing technologies are greatly increasing the capacity to identify these variations. Given the large number of variations now being discovered, computational methods to prioritize the functional importance of genetic variations are of growing interest. Thus far, the focus of computational tools has been mainly on the prediction of the effects of amino acid changing single nucleotide polymorphisms (SNPs) and little attention has been paid to indels or nonsense SNPs that result in premature stop codons. RESULTS: We propose computational methods to rank insertion-deletion mutations in the coding as well as non-coding regions and nonsense mutations. We rank these variations by measuring the extent of their effect on biological function, based on the assumption that evolutionary conservation reflects function. Using sequence data from budding yeast and human, we show that variations which that we predict to have larger effects segregate at significantly lower allele frequencies, and occur less frequently than expected by chance, indicating stronger purifying selection. Furthermore, we find that insertions, deletions and premature stop codons associated with disease in the human have significantly larger predicted effects than those not associated with disease. Interestingly, the large-effect mutations associated with disease show a similar distribution of predicted effects to that expected for completely random mutations. CONCLUSIONS: This demonstrates that the evolutionary conservation context of the sequences that harbour insertions, deletions and nonsense mutations can be used to predict and rank the effects of the mutations.