Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this "proteogenomics" approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy.

The γδ IEL effector API5 masks genetic susceptibility to Paneth cell death.

Loss of Paneth cells and their antimicrobial granules compromises the intestinal epithelial barrier and is associated with Crohn's disease, a major type of inflammatory bowel disease1-7. Non-classical lymphoid cells, broadly referred to as intraepithelial lymphocytes (IELs), intercalate the intestinal epithelium8,9. This anatomical position has implicated them as first-line defenders in resistance to infections, but their role in inflammatory disease pathogenesis requires clarification. The identification of mediators that coordinate crosstalk between specific IEL and epithelial subsets could provide insight into intestinal barrier mechanisms in health and disease. Here we show that the subset of IELs that express γ and δ T cell receptor subunits (γδ IELs) promotes the viability of Paneth cells deficient in the Crohn's disease susceptibility gene ATG16L1. Using an ex vivo lymphocyte-epithelium co-culture system, we identified apoptosis inhibitor 5 (API5) as a Paneth cell-protective factor secreted by γδ IELs. In the Atg16l1-mutant mouse model, viral infection induced a loss of Paneth cells and enhanced susceptibility to intestinal injury by inhibiting the secretion of API5 from γδ IELs. Therapeutic administration of recombinant API5 protected Paneth cells in vivo in mice and ex vivo in human organoids with the ATG16L1 risk allele. Thus, we identify API5 as a protective γδ IEL effector that masks genetic susceptibility to Paneth cell death.

Hyperactive CDK2 Activity in Basal-like Breast Cancer Imposes a Genome Integrity Liability that Can Be Exploited by Targeting DNA Polymerase ε.

Knowledge of fundamental differences between breast cancer subtypes has driven therapeutic advances; however, basal-like breast cancer (BLBC) remains clinically intractable. Because BLBC exhibits alterations in DNA repair enzymes and cell-cycle checkpoints, elucidation of factors enabling the genomic instability present in this subtype has the potential to reveal novel anti-cancer strategies. Here, we demonstrate that BLBC is especially sensitive to suppression of iron-sulfur cluster (ISC) biosynthesis and identify DNA polymerase epsilon (POLE) as an ISC-containing protein that underlies this phenotype. In BLBC cells, POLE suppression leads to replication fork stalling, DNA damage, and a senescence-like state or cell death. In contrast, luminal breast cancer and non-transformed mammary cells maintain viability upon POLE suppression but become dependent upon an ATR/CHK1/CDC25A/CDK2 DNA damage response axis. We find that CDK1/2 targets exhibit hyperphosphorylation selectively in BLBC tumors, indicating that CDK2 hyperactivity is a genome integrity vulnerability exploitable by targeting POLE.

Single-Cell Analysis of CX3CR1+ Cells Reveals a Pathogenic Role for BIRC5+ Myeloid Proliferating Cells Driven by Staphylococcus aureus Leukotoxins.

Our previous studies identified a population of stem cell-like proliferating myeloid cells within inflamed tissues that could serve as a reservoir for tissue macrophages to adopt different activation states depending on the microenvironment. By lineage-tracing cells derived from CX3CR1+ precursors in mice during infection and profiling by single-cell RNA sequencing, in this study, we identify a cluster of BIRC5+ myeloid cells that expanded in the liver during chronic infection with either the parasite Schistosoma mansoni or the bacterial pathogen Staphylococcus aureus. In the absence of tissue-damaging toxins, S. aureus infection does not elicit these BIRC5+ cells. Moreover, deletion of BIRC5 from CX3CR1-expressing cells results in improved survival during S. aureus infection. Hence the combination of single-cell RNA sequencing and genetic fate-mapping CX3CR1+ cells revealed a toxin-dependent pathogenic role for BIRC5 in myeloid cells during S. aureus infection.

PhosphoDisco: A Toolkit for Co-regulated Phosphorylation Module Discovery in Phosphoproteomic Data.

Kinases are key players in cancer-relevant pathways and are the targets of many successful precision cancer therapies. Phosphoproteomics is a powerful approach to study kinase activity and has been used increasingly for the characterization of tumor samples leading to the identification of novel chemotherapeutic targets and biomarkers. Finding co-regulated phosphorylation sites which represent potential kinase-substrate sets or members of the same signaling pathway allows us to harness these data to identify clinically relevant and targetable alterations in signaling cascades. Unfortunately, studies have found that databases of co-regulated phosphorylation sites are only experimentally supported in a small number of substrate sets. To address the inherent challenge of defining co-regulated phosphorylation modules relevant to a given dataset, we developed PhosphoDisco, a toolkit for determining co-regulated phosphorylation modules. We applied this approach to tandem mass spectrometry based phosphoproteomic data for breast and non-small cell lung cancer and identified canonical as well as putative new phosphorylation site modules. Our analysis identified several interesting modules in each cohort. Among these was a new cell cycle checkpoint module enriched in basal breast cancer samples and a module of PRKC isozymes putatively co-regulated by CDK12 in lung cancer. We demonstrate that modules defined by PhosphoDisco can be used to further personalized cancer treatment strategies by establishing active signaling pathways in a given patient tumor or set of tumors, and in providing new ways to classify tumors based on signaling activity.

Staphylococcus aureus induces a muted host response in human blood that blunts the recruitment of neutrophils.

Staphylococcus aureus is an opportunistic pathogen and chief among bloodstream-infecting bacteria. S. aureus produces an array of human-specific virulence factors that may contribute to immune suppression. Here, we defined the response of primary human phagocytes following infection with S. aureus using RNA-sequencing (RNA-Seq). We found that the overall transcriptional response to S. aureus was weak both in the number of genes and in the magnitude of response. Using an ex vivo bacteremia model with fresh human blood, we uncovered that infection with S. aureus resulted in the down-regulation of genes related to innate immune response and cytokine and chemokine signaling. This muted transcriptional response was conserved across diverse S. aureus clones but absent in blood exposed to heat-killed S. aureus or blood infected with the less virulent staphylococcal species Staphylococcus epidermidis. Notably, this signature was also present in patients with S. aureus bacteremia. We identified the master regulator S. aureus exoprotein expression (SaeRS) and the SaeRS-regulated pore-forming toxins as key mediators of the transcriptional suppression. The S. aureus-mediated suppression of chemokine and cytokine transcription was reflected by circulating protein levels in the plasma. Wild-type S. aureus elicited a soluble milieu that was restrictive in the recruitment of human neutrophils compared with strains lacking saeRS. Thus, S. aureus blunts the inflammatory response resulting in impaired neutrophil recruitment, which could promote the survival of the pathogen during invasive infection.

Biomarkers and cardiovascular events in patients with stable coronary disease in the ISCHEMIA Trials.

IMPORTANCE: Biomarkers may improve prediction of cardiovascular events for patients with stable coronary artery disease (CAD), but their importance in addition to clinical tests of inducible ischemia and CAD severity is unknown. OBJECTIVES: To evaluate the prognostic value of multiple biomarkers in stable outpatients with obstructive CAD and moderate or severe inducible ischemia. DESIGN AND SETTING: The ISCHEMIA and ISCHEMIA CKD trials randomized 5,956 participants with CAD to invasive or conservative management from July 2012 to January 2018; 1,064 participated in the biorepository. MAIN OUTCOME MEASURES: Primary outcome was cardiovascular death, myocardial infarction (MI), or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. Secondary outcome was cardiovascular death or MI. Improvements in prediction were assessed by cause-specific hazard ratios (HR) and area under the receiver operating characteristics curve (AUC) for an interquartile increase in each biomarker, controlling for other biomarkers, in a base clinical model of risk factors, left ventricular ejection fraction (LVEF) and ischemia severity. Secondary analyses were performed among patients in whom core-lab confirmed severity of CAD was ascertained by computed cardiac tomographic angiography (CCTA). EXPOSURES: Baseline levels of interleukin-6 (IL-6), high sensitivity troponin T (hsTnT), growth differentiation factor 15 (GDF-15), N-terminal pro-B-type natriuretic peptide (NT-proBNP), lipoprotein a (Lp[a]), high sensitivity C-reactive protein (hsCRP), Cystatin C, soluble CD 40 ligand (sCD40L), myeloperoxidase (MPO), and matrix metalloproteinase 3 (MMP3). RESULTS: Among 757 biorepository participants, median (IQR) follow-up was 3 (2-5) years, age was 67 (61-72) years, and 144 (19%) were female; 508 had severity of CAD by CCTA available. In an adjusted multimarker model with hsTnT, GDF-15, NT-proBNP and sCD40L, the adjusted HR for the primary outcome per interquartile increase in each biomarker was 1.58 (95% CI 1.22, 2.205), 1.60 (95% CI 1.16, 2.20), 1.61 (95% 1.22, 2.14), and 1.46 (95% 1.12, 1.90), respectively. The adjusted multimarker model also improved prediction compared with the clinical model, increasing the AUC from 0.710 to 0.792 (P < .01) and 0.714 to 0.783 (P < .01) for the primary and secondary outcomes, respectively. Similar findings were observed after adjusting for core-lab confirmed atherosclerosis severity. CONCLUSIONS AND RELEVANCE: Among ISCHEMIA biorepository participants, biomarkers of myocyte injury/distension, inflammation, and platelet activity improved cardiovascular event prediction in addition to risk factors, LVEF, and assessments of ischemia and atherosclerosis severity. These biomarkers may improve risk stratification for patients with stable CAD.

Modeling of clinical phenotypes in systemic lupus erythematosus based on the platelet transcriptome and FCGR2a genotype.

BACKGROUND: The clinical heterogeneity of SLE with its complex pathogenesis remains challenging as we strive to provide optimal management. The contribution of platelets to endovascular homeostasis, inflammation and immune regulation highlights their potential importance in SLE. Prior work from our group showed that the Fcγ receptor type IIa (FcγRIIa)-R/H131 biallelic polymorphism is associated with increased platelet activity and cardiovascular risk in SLE. The study was initiated to investigate the platelet transcriptome in patients with SLE and evaluate its association across FcγRIIa genotypes and distinct clinical features. METHODS: Fifty-one patients fulfilling established criteria for SLE (mean age = 41.1 ± 12.3, 100% female, 45% Hispanic, 24% black, 22% Asian, 51% white, mean SLEDAI = 4.4 ± 4.2 at baseline) were enrolled and compared with 18 demographically matched control samples. The FCGR2a receptor was genotyped for each sample, and RNA-seq was performed on isolated, leukocyte-depleted platelets. Transcriptomic data were used to create a modular landscape to explore the differences between SLE patients and controls and various clinical parameters in the context of FCGR2a genotypes. RESULTS: There were 2290 differentially expressed genes enriched for pathways involved in interferon signaling, immune activation, and coagulation when comparing SLE samples vs controls. When analyzing patients with proteinuria, modules associated with oxidative phosphorylation and platelet activity were unexpectedly decreased. Furthermore, genes that were increased in SLE and in patients with proteinuria were enriched for immune effector processes, while genes increased in SLE but decreased in proteinuria were enriched for coagulation and cell adhesion. A low-binding FCG2Ra allele (R131) was associated with decreases in FCR activation, which further correlated with increases in platelet and immune activation pathways. Finally, we were able to create a transcriptomic signature of clinically active disease that performed significantly well in discerning SLE patients with active clinical disease form those with inactive clinical disease. CONCLUSIONS: In aggregate, these data demonstrate the platelet transcriptome provides insight into lupus pathogenesis and disease activity, and shows potential use as means of assessing this complex disease using a liquid biopsy.

Multimodal single-cell analysis of cutaneous T-cell lymphoma reveals distinct subclonal tissue-dependent signatures.

Cutaneous T-cell lymphoma (CTCL) is a heterogeneous group of mature T-cell neoplasms characterized by the accumulation of clonal malignant CD4+ T cells in the skin. The most common variant of CTCL, mycosis fungoides (MF ), is confined to the skin in early stages but can be accompanied by extracutaneous dissemination of malignant T cells to the blood and lymph nodes in advanced stages of disease. Sézary syndrome (SS), a leukemic form of disease, is characterized by significant blood involvement. Little is known about the transcriptional and genomic relationship between skin- and blood-residing malignant T cells in CTCL. To identify and interrogate malignant clones in matched skin and blood from patients with leukemic MF and SS, we combine T-cell receptor clonotyping with quantification of gene expression and cell surface markers at the single cell level. Our data reveal clonal evolution at a transcriptional and genetic level within the malignant populations of individual patients. We highlight highly consistent transcriptional signatures delineating skin- and blood-derived malignant T cells. Analysis of these 2 populations suggests that environmental cues, along with genetic aberrations, contribute to transcriptional profiles of malignant T cells. Our findings indicate that the skin microenvironment in CTCL promotes a transcriptional response supporting rapid malignant expansion, as opposed to the quiescent state observed in the blood, potentially influencing efficacy of therapies. These results provide insight into tissue-specific characteristics of cancerous cells and underscore the need to address the patients' individual malignant profiles at the time of therapy to eliminate all subclones.

An inflammatory transcriptomic signature in psoriasis associates with future cardiovascular events.

BACKGROUND: Psoriasis is an inflammatory skin disease associated with increased cardiovascular (CV) risk, whose pathogenesis is not fully known. OBJECTIVE: We identified a transcriptomic signature in psoriasis and investigated its association with prevalent and future risk of a CV event to understand the connection between psoriasis and CV disease (CVD). METHODS: Psoriasis patients (n = 37) with a history of moderate-severe skin disease without CVD and 11 matched controls underwent whole blood RNA sequencing. This transcriptomic signature in psoriasis versus controls was evaluated in two CVD cohorts: Women referred for cardiac catheterization with (n = 76) versus without (n = 97) myocardial infarction (MI), and patients with peripheral artery disease (n = 106) followed over 2.5 years for major adverse CV or limb events (MACLE). The association between genes differentially expressed in psoriasis and prevalent and incident CV events was assed. RESULTS: In psoriasis, median age was 44 (IQR; 34-51) years, 49% male and ACC/AHA ASCVD Risk Score of 1.0% (0.6-3.4) with no significant difference versus controls. The median psoriasis area and severity index score (PASI) was 4.0 (IQR 2.9-8.2) with 36% on biologic therapy. Overall, 247 whole blood genes were upregulated and 228 downregulated in psoriasis versus controls (p < 0.05), and 1302 genes positively and 1244 genes negatively correlated with PASI (p < 0.05). Seventy-three genes overlapped between psoriasis prevalence and PASI with key regulators identified as IL-6, IL-1ß and interferon gamma. In the CVD cohorts, 50 of 73 genes (68%) identified in psoriasis associated with prevalent MI, and 29 (40%) with incident MACLE. Key regulator transcripts identified in psoriasis and CVD cohorts included SOCS3, BCL3, OSM, PIM2, PIM3 and STAT5A. CONCLUSIONS: A whole blood transcriptomic signature of psoriasis diagnosis and severity associated with prevalent MI and incident MACLE. These data have implications for better understanding the link between psoriasis, systemic inflammation and CVD.

Single-Cell Transcriptional Survey of Ileal-Anal Pouch Immune Cells From Ulcerative Colitis Patients.

BACKGROUND & AIMS: Restorative proctocolectomy with ileal pouch-anal anastomosis is a surgical procedure in patients with ulcerative colitis refractory to medical therapies. Pouchitis, the most common complication, is inflammation of the pouch of unknown etiology. To define how the intestinal immune system is distinctly organized during pouchitis, we analyzed tissues from patients with and without pouchitis and from patients with ulcerative colitis using single-cell RNA sequencing (scRNA-seq). METHODS: We examined pouch lamina propria CD45+ hematopoietic cells from intestinal tissues of ulcerative colitis patients with (n = 15) and without an ileal pouch-anal anastomosis (n = 11). Further in silico meta-analysis was performed to generate transcriptional interaction networks and identify biomarkers for patients with inflamed pouches. RESULTS: In addition to tissue-specific signatures, we identified a population of IL1B/LYZ+ myeloid cells and FOXP3/BATF+ T cells that distinguish inflamed tissues, which we further validated in other scRNA-seq datasets from patients with inflammatory bowel disease (IBD). Cell-type-specific transcriptional markers obtained from scRNA-seq was used to infer representation from bulk RNA sequencing datasets, which further implicated myeloid cells expressing IL1B and S100A8/A9 calprotectin as interacting with stromal cells, and Bacteroidales and Clostridiales bacterial taxa. We found that nonresponsiveness to anti-integrin biologic therapies in patients with ulcerative colitis was associated with the signature of IL1B+/LYZ+ myeloid cells in a subset of patients. CONCLUSIONS: Features of intestinal inflammation during pouchitis and ulcerative colitis are similar, which may have clinical implications for the management of pouchitis. scRNA-seq enables meta-analysis of multiple studies, which may facilitate the identification of biomarkers to personalize therapy for patients with IBD. The processed single cell count tables are provided in Gene Expression Omnibus; GSE162335. Raw sequence data are not public and are protected by controlled-access for patient privacy.

Gene Expression Signature in Patients With Symptomatic Peripheral Artery Disease.

[Figure: see text].

Distinct Features of Human Myeloid Cell Cytokine Response Profiles Identify Neutrophil Activation by Cytokines as a Prognostic Feature during Tuberculosis and Cancer.

Myeloid cells are a vital component of innate immunity and comprise monocytes, macrophages, dendritic cells, and granulocytes. How myeloid cell lineage affects activation states in response to cytokines remains poorly understood. The cytokine environment and cellular infiltrate during an inflammatory response may contain prognostic features that predict disease outcome. In this study, we analyzed the transcriptional responses of human monocytes, macrophages, dendritic cells, and neutrophils in response to stimulation by IFN-γ, IFN-ß, IFN-λ, IL-4, IL-13, and IL-10 cytokines to better understand the heterogeneity of activation states in inflammatory conditions. This generated a myeloid cell-cytokine-specific response matrix that can infer representation of myeloid cells and the cytokine environment they encounter during infection, in tumors and in whole blood. Neutrophils were highly responsive to type 1 and type 2 cytokine stimulation but did not respond to IL-10. We identified transcripts specific to IFN-ß stimulation, whereas other IFN signature genes were upregulated by both IFN-γ and IFN-ß. When we used our matrix to deconvolute blood profiles from tuberculosis patients, the IFN-ß-specific neutrophil signature was reduced in tuberculosis patients with active disease, whereas the shared response to IFN-γ and IFN-ß in neutrophils was increased. When applied to glioma patients, transcripts of neutrophils exposed to IL-4/IL-13 and monocyte responses to IFN-γ or IFN-ß emerged as opposing predictors of patient survival. Hence, by dissecting how different myeloid cells respond to cytokine activation, we can delineate biological roles for myeloid cells in different cytokine environments during disease processes, especially during infection and tumor progression.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

BlackSheep: A Bioconductor and Bioconda Package for Differential Extreme Value Analysis.

Unbiased assays such as shotgun proteomics and RNA-seq provide high-resolution molecular characterization of tumors. These assays measure molecules with highly varied distributions, making interpretation and hypothesis testing challenging. Samples with the most extreme measurements for a molecule can reveal the most interesting biological insights yet are often excluded from analysis. Furthermore, rare disease subtypes are, by definition, underrepresented in cancer cohorts. To provide a strategy for identifying molecules aberrantly enriched in small sample cohorts, we present BlackSheep, a package for nonparametric description and differential analysis of genome-wide data, available from Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/blacksheepr.html) and Bioconda (https://bioconda.github.io/recipes/blksheep/README.html). BlackSheep is a complementary tool to other differential expression analysis methods, which is particularly useful when analyzing small subgroups in a larger cohort.

Hypercluster: a flexible tool for parallelized unsupervised clustering optimization.

BACKGROUND: Unsupervised clustering is a common and exceptionally useful tool for large biological datasets. However, clustering requires upfront algorithm and hyperparameter selection, which can introduce bias into the final clustering labels. It is therefore advisable to obtain a range of clustering results from multiple models and hyperparameters, which can be cumbersome and slow. RESULTS: We present hypercluster, a python package and SnakeMake pipeline for flexible and parallelized clustering evaluation and selection. Users can efficiently evaluate a huge range of clustering results from multiple models and hyperparameters to identify an optimal model. CONCLUSIONS: Hypercluster improves ease of use, robustness and reproducibility for unsupervised clustering application for high throughput biology. Hypercluster is available on pip and bioconda; installation, documentation and example workflows can be found at: https://github.com/ruggleslab/hypercluster .

Loss of HDAC6 alters gut microbiota and worsens obesity.

Alterations in gut microbiota are known to affect intestinal inflammation and obesity. Antibiotic treatment can affect weight gain by elimination of histone deacetylase (HDAC) inhibitor-producing microbes, which are anti-inflammatory by augmenting regulatory T (Treg) cells. We asked whether mice that lack HDAC6 and have potent suppressive Treg cells are protected from microbiota-induced accelerated weight gain. We crossed wild-type and HDAC6-deficient mice and subjected the offspring to perinatal penicillin, inducing weight gain via microbiota disturbance. We observed that male HDAC6-deficient mice were not protected and developed profoundly accelerated weight gain. The antibiotic-exposed HDAC6-deficient mice showed a mixed immune phenotype with increased CD4+ and CD8+ T-cell activation yet maintained the enhanced Treg cell-suppressive function phenotype characteristic of HDAC6-deficient mice. 16S rRNA sequencing of mouse fecal samples reveals that their microbiota diverged with time, with HDAC6 deletion altering microbiome composition. On a high-fat diet, HDAC6-deficient mice were depleted in representatives of the S24-7 family and Lactobacillus but enriched with Bacteroides and Parabacteroides; these changes are associated with obesity. Our findings further our understanding of the influence of HDACs on microbiome composition and are important for the development of HDAC6 inhibitors in the treatment of human diseases.-Lieber, A. D., Beier, U. H., Xiao, H., Wilkins, B. J., Jiao, J., Li, X. S., Schugar, R. C., Strauch, C. M., Wang, Z., Brown, J. M., Hazen, S. L., Bokulich, N. A., Ruggles, K. V., Akimova, T., Hancock, W. W., Blaser, M. J. Loss of HDAC6 alters gut microbiota and worsens obesity.

Methods, Tools and Current Perspectives in Proteogenomics.

With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data.

BACKGROUND: Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. RESULTS: We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. CONCLUSIONS: WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

RIVET: comprehensive graphic user interface for analysis and exploration of genome-wide translatomics data.

BACKGROUND: Translatomics data, particularly genome-wide ribosome profiling and polysome profiling, provide multiple levels of gene regulatory information that can be used to assess general transcription and translation, as well translational efficiency. The increasing popularity of these techniques has resulted in multiple algorithms to detect translational regulation, typically distributed in the form of command line tools that require a basic level of programming ability. Additionally, due to the static nature of current software, dynamic transcriptional and translational comparative analysis cannot be adequately achieved. In order to streamline hypothesis generation, investigators must have the ability to manipulate and interact with their data in real-time. RESULTS: To address the lack of integration in current software, we introduce RIVET, Ribosomal Investigation and Visualization to Evaluate Translation, an R shiny based graphical user interface for translatomics data exploration and differential analysis. RIVET can analyze either microarray or RNA sequencing data from polysome profiling and ribosome profiling experiments. RIVET provides multiple choices for statistical analysis as well as integration of transcription, translation, and translational efficiency data analytics and the ability to visualize all results dynamically. CONCLUSIONS: RIVET is a user-friendly tool designed for bench scientists with little to no programming background. RIVET facilitates the data analysis of translatomics data allowing for dynamic generation of results based on user-defined inputs and publication ready visualization. We expect RIVET will allow for scientists to efficiently make more comprehensive data observations that will lead to more robust hypothesis regarding translational regulation.