The improved model of Escherichia coli with underground metabolism. The model is provided as a MATLAB file compatible with the COBRA toolbox. It includes the reactions in the latest iJO1366 reconstruction, as well as underground metabolism and new gene-protein-reaction associations. The resulting model contains 1380 genes, 3027 reactions (including exchange reactions), and 2151 metabolites. (MAT 214 kb)

Flux rates of Colombos conditions. Full list of Colombos conditions and the corresponding flux rates predicted using trilevel linear programming. (XLSX 364 kb)

Spatial omics technologies have revolutionized the field of biology by enabling the visualization of biomolecules within their native tissue context. However, the high costs associated with proprietary instrumentation, specialized reagents, and complex workflows have limited the broad application of these techniques. In this study, we introduce Python-based Robotic Imaging and Staining for Modular Spatial omics (PRISMS), an open-sourced, automated multiplexing pipeline compatible with several sample types and Nikon NIS Elements Basic Research software. PRISMS utilizes a liquid handling robot with thermal control to enable rapid, automated staining of RNA and protein samples. The modular sample holders and Python control facilitate high-throughput, single-molecule fluorescence imaging on widefield and confocal microscopes.We successfully demonstrate the versatility of PRISMS by imaging tissue slides and adherent cells. We also show that PRISMS can be used to perform super-resolved imaging, such as super-resolution radial fluctuations (SRRF) 1. PRISMS is a powerful tool that can be used to democratize spatial omics by providing researchers with an accessible, reproducible, and cost-effective solution for multiplex imaging. Specifically, PRISMS is an open-sourced, automated multiplexing pipeline for spatial omics, is compatible with several sample types and Nikon NIS Elements Basic Research software, performs high-throughput, single-molecule fluorescence imaging on widefield and confocal microscopes, and can be used to perform super-resolved imaging, such as SRRF. Overall, PRISMS is a powerful tool that can be used to democratize spatial omics by providing researchers with an accessible, reproducible, and cost-effective solution for multiplex imaging. This open-source platform will enable researchers to push the boundaries of spatial biology and make groundbreaking discoveries.

This paper discusses digital spatial RNA profiling (DSP) and imaging mass cytometry (IMC) data that were generated in patients with inflammatory bowel disease and/or colitis-associated dysplasia. In this Verse, raw data and R scripts have been deposited.

This paper discusses digital spatial RNA profiling (DSP) and imaging mass cytometry (IMC) data that were generated in patients with inflammatory bowel disease and/or colitis-associated dysplasia. In this Verse, raw data and R scripts have been deposited.

Background: Multi-omics analyses are profitable for discovering novel biomarkers and drug targets, but such integrated examinations on mitochondria of colorectal cancer (CRC) patients are lacking. Methods: We investigated global structural variants, DNA methylation, chromatin accessibility, proteome, and phosphoproteome on human CRC (n = 6-8). The alterations of mitochondria on these levels and potential upstream regulatory genes were described. Furthermore, combining with the mRNA datasets of 538 CRC and 91 colitis patients from the public databases, we identified independent prognostic factors (IPFs). Findings: Revealed by the proteogenomic analyses in our study, mitochondria altered the most among all organelles in CRC, which were also associated with patient prognosis the most. We found that the mRNA of one nuclear-coding mitochondrial gene (NCMG), HIGD1A, decreased in colitis, two subtypes of adenoma, and six subtypes of CRC, subsequently was identified as a favorable IPF for CRC. Besides, the comprehensive analyses of mitochondria by multi-omics uncovered unique proteogenomic alterations on six survival-related NCMGs. Key transcriptional factors potentially regulating the mitochondria were also unveiled, such as GLIS1, JUN, CREB1, and YAP1. Finally, p38 was highlighted as one possible central kinase involving in the modulation of mitochondrial activity in CRC patients. Interpretation: Our study presents a multilayer and molecular picture of mitochondria of CRC patients, recognizes HIGD1A as a potential prognostic biomarker, and provides new candidate genes as therapeutic targets

Additional file6: ORA with Reactome Pathways and AMEND Module from OGT-KO Data. Complete list of significant Reactome pathways from ORA on the AMEND module from the OGT-KO data analysis. Significance level was set to 0.05 after adjustment for multiple testing using the Benjamini-Hochberg method

The recent advance in targeted label-free proteomics, SWATH-MS, can provide consistent protein detection and reproducible protein quantitation, which is a considerable advantage for biomarker study of urinary exosome-enriched extracellular vesicles (EVs). We developed a SWATH-MS workflow with a curated spectral library of 1,073 targets. Application of the workflow across nine replicates of three sample types (EVs, microvesicles (MVs) and urine proteins (UP)) resulting in the quantitation of 842 proteins. The median-coefficient of variation of the 842 proteins in the EV sample was 7.6%, indicating excellent reproducibility. Data analysis showed common EV markers, (i.e. CD9, CD63, ALIX, TSG101 and HSP70) were enriched in urinary EVs as compared to MV and UP samples. Further development and applicationof this SWATH-MS workflow to a variety of kidney diseases may allow for new and robust avenues for biomarker identification and validation for clinical use.

Quantitative analysis of proteomes across multiple time points, organelles, and perturbations is essential for understanding both fundamental biology and disease states. The development of isobaric tags (e.g. TMT) have enabled the simultaneous measurement of peptide abundances across several different conditions. These multiplexed approaches are promising in principle because of advantages in throughput and measurement quality. However, in practice existing multiplexing approaches suffer from key limitations. In its simple implementation (TMT-MS2), measurements are distorted by chemical noise leading to poor measurement accuracy. The current state-of-the-art (TMT-MS3) addresses this, but requires specialized quadrupole-iontrap-Orbitrap instrumentation. The complement reporter ion approach (TMTc) produces high accuracy measurements and is compatible with many more instruments, like quadrupole-Orbitraps. However, the required deconvolution of the TMTc cluster leads to poor measurement precision. Here, we introduce TMTc+, which adds the modeling of the MS2-isolation step into the deconvolution algorithm. The resulting measurements are comparable in precision to TMT-MS3/MS2. The improved duty cycle, and lower filtering requirements make TMTc+ more sensitive than TMT-MS3 and comparable with TMT-MS2. At the same time, unlike TMT-MS2, TMTc+ is exquisitely able to distinguish signal from chemical noise even outperforming TMT-MS3. Lastly, we compare TMTc+ to quantitative label-free proteomics of total HeLa lysate and find that TMTc+ quantifies 7.8k versus 3.9k proteins in a 5-plex sample. At the same time the median coefficient of variation improves from 13% to 4%. Thus, TMTc+ advances quantitative proteomics by enabling accurate, sensitive, and precise multiplexed experiments on more commonly used instruments.

Additional file4: ORA with GO Terms and AMEND Module from TCGA-KIRC Data. Complete list of significant Gene Ontologyterms from ORA on the AMEND module from the TCGA-KIRC data analysis. Significance level was set to 0.01 after adjustment for multiple testing using the Benjamini-Hochberg method

Immuno-LC-PRM assay was developed to simultaneously quantify the expression levels of six immune markers (CD8A, CD4, LAG3, PD1, PD-L1 and PD-L2) using as little as 1-2 mg of fresh frozen tissue.

Sample multiplexing-based proteomic strategies rely on fractionation to improve proteome coverage. Tandem mass tag (TMT) experiments, for example, can currently accommodate up to 18 samples with proteins spanning several orders of magnitude, thus necessitating fractionation to achieve reasonable proteome coverage. Here, we present a simple yet effective peptide fractionation strategy that partitions a pooled TMT sample with a two-step elution using a strong anion exchange (SAX) spin column prior to gradient-based basic pH reversed-phase (BPRP) fractionation. We highlight our strategy with a TMTpro18-plex experiment using nine diverse human cell lines in biological duplicate. We collected three datasets, one using only BPRP fractionation, and two others of each SAX-partition followed by BPRP. The three datasets quantified a similar number of proteins and peptides, and the data highlight noticeable differences in the distribution of peptide charge and isoelectric point between the SAX partitions. The combined SAX partition dataset contributed 10% more proteins and 20% more unique peptides that were not quantified by BPRP fractionation alone. In addition to this improved fractionation strategy, we provide an online resource of relative abundance profiles for over 11,000 proteins across the nine human cell lines investigated herein.

Goal of this experiment was the differentiation of direct targets of induced degradation of the JQ1-PROTAC from downstream regulatory effects.

SARS-CoV-2 infection can manifest as a wide range of respiratory and systemic symptoms well after the acute phase of infection in over 50% of patients. Key questions remain on the long-term effect of infection on tissue pathology and on recovered COVID-19 patients. Here we perform multiplexed imaging of post-mortem lung tissue from 12 individuals that died post-acute COVID-19 (PC) and compare them to patients who died during the acute phase of COVID-19, patients who died with idiopathic pulmonary fibrosis (IPF), and otherwise healthy lung. We find evidence of viral presence in the lung up to 359 days after the acute phase of disease, often in patients with negative nasopharyngeal swab test. Our analyses identify accumulation of senescent alveolar type 2 cells, fibrosis with hypervascularization of peribronchial areas and alveolar septa, as the most pronounced pathophysiological features seen in the lung of PC patients. At the cellular level, lung disease of PC patients is distinct from the chronic pulmonary disease of IPF but shares pathological features which may help rationalize interventions for PASC patients. Altogether, this study provides an important ground for the understanding of the long-term effects of SARS-CoV-2 infection at the microanatomical, cellular and molecular level.

Management of severe malaria remains a critical global challenge. In this study, using a multiplexed quantitative proteomics pipeline we systematically investigated the plasma proteome alterations in non-severe and severe malaria patients. We identified a few parasite proteins in severe malaria patients, which could be promising from a diagnostic perspective. Further, from host proteome analysis we observed substantial modulations in many crucial physiological pathways, including lipid metabolism, cytokine signaling, complement, and coagulation cascades in severe malaria. We propose that severe manifestations of malaria are possibly underpinned by modulations of the host physiology and defense machinery, which is evidently reflected in the plasma proteome alterations. Importantly, we identified multiple blood markers that can effectively define different complications of severe falciparum malaria, including cerebral syndromes and severe anemia. The ability of our identified blood markers to distinguish different severe complications of malaria may aid in developing new clinical tests for monitoring malaria severity.

Introduction

Hepatocellular carcinoma (HCC) remains a significant contributor to cancer-related deaths. Immunotherapy, either alone or in combination, has emerged as the standard treatment for advanced HCC. Notably, the combination of durvalumab (dur) and tremelimumab (trem) has received FDA approval based on findings from the HIMALAYA trial. However, comprehensive studies elucidating immune responses are lacking. We conducted a thorough analysis utilizing clinical samples from tumor biopsies to understand the mechanism of response.

Methods

Multiplexed immunofluorescence microscopy was used to analyze immune cell infiltration in primary human liver cancer samples. We developed and validated a comprehensive 37-plex antibody panel for immunofluorescence imaging of human FFPE samples. We applied highly multiplexed co-detection by indexing (CODEX) technology to simultaneously profile in situ expression of 37 proteins at sub-cellular resolution in 20 HCC patient samples using whole slide scanning. We established an image analysis pipeline to quantify all major cell populations in the human liver using supervised manual gating and unsupervised clustering algorithms using the exported matrix of the marker expression and spatial information. Clinical metadata including sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples.

Results

Using high-dimensional spatially resolved quantitative analysis of multiplexed immunofluorescence microscopy images, we generated a unique dataset and profiled the single-cell pathology landscape for human HCC treated with immunotherapy. In situ phenotyping of 400,000 single cells (including 130,000 CD45+ immune cells) allowed for the quantification of cell phenotype clusters, differential analysis of activation markers, and spatial features of each individual cell. This analysis revealed the comprehensive profile of the cell composition and spatial interactions of different cells in the TiME of patients treated with immunotherapy. Further details on the study can be obtained in our paper once it’s published.

Conclusion

We developed the CODEX panel for FFPE biopsy samples of HCC patients.

Additional file2: Molecular Interaction Network Characteristics. Descriptions of the molecular interaction networks involved in this study, including node type, associated evaluation task, interaction type, source, species, pre-processing, and node & edge counts

There are three datasets in this entry: the COVIDOme Sample Metadata, the COVIDome SOMAscan dataset, and the COVIDome MSD Cytokine Dataset. These datasets were generated by the COVIDome Project at the University of Colorado Anschutz Medical Campus. To learn more about the COVIDome Project please visit covidome.org. This project aims to accelerate translational research in the field of COVID19 by generating and broadly sharing multi-omics datasets of research participants with and without COVID19.

The Sample Metadata file describes sample ID, COVID19 status at the time of blood draw (positive or negative), sex and age. The SOMAscan dataset is a plasma proteomics dataset obtained from research participants with and without COVID19 using the SOMAscan® technology. The MSD cytokine dataset was generated using multiplex immunoassays with Meso Scale Discovery (MSD) technology.

Despite the increasing prevalence of patients with Long Covid Syndrome (LCS), to date the pathophysiology of the disease is still unclear, and therefore diagnosis and therapy are a complex effort without any standardization. To address these issues, we performed a broad exploratory screening study applying state-of-the-art post-genomic profiling methods to blood plasma derived from three groups: 1) healthy individuals vaccinated against SARS-CoV-2 without exposure to the full virus, 2) asymptomatic fully recovered patients at least three months after SARS-CoV-2 infection, 3) symptomatic patients at least 3 months after a SARS-CoV-2 infection, here designated as Long Covid Syndrome (LCS) patients. Multiplex cytokine profiling indicated slightly elevated cytokine levels in recovered individuals in contrast to LCS patients, who displayed lowest levels of cytokines. Label-free proteome profiling corroborated an anti-inflammatory status in LCS characterized by low acute phase protein levels and a uniform down-regulation of macrophagederived secreted proteins, a pattern also characteristic for chronic fatigue syndrome (CFS). Along those lines, eicosanoid and docosanoid analysis revealed high levels of omega-3 fatty acids and a prevalence of anti-inflammatory oxylipins in LCS patients compared to the other study groups. Targeted metabolic profiling indicated low amino acid and triglyceride levels and deregulated acylcarnithines, characteristic for CFS and indicating mitochondrial stress in LCS patients. The anti-inflammatory osmolytes taurine and hypaphorine were significantly up-regulated in LCS patients. In summary, here we present evidence for a specific anti-inflammatory and highly characteristic metabolic signature in LCS which could serve for future diagnostic purposes and help to establish rational therapeutic interventions in these patients.