Complex changes in serum protein levels in COVID-19 convalescents.

The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.

Ring Finger 149-Related Is an FGF/MAPK-Independent Regulator of Pharyngeal Muscle Fate Specification.

During embryonic development, cell-fate specification gives rise to dedicated lineages that underlie tissue formation. In olfactores, which comprise tunicates and vertebrates, the cardiopharyngeal field is formed by multipotent progenitors of both cardiac and branchiomeric muscles. The ascidian Ciona is a powerful model to study cardiopharyngeal fate specification with cellular resolution, as only two bilateral pairs of multipotent cardiopharyngeal progenitors give rise to the heart and to the pharyngeal muscles (also known as atrial siphon muscles, ASM). These progenitors are multilineage primed, in as much as they express a combination of early ASM- and heart-specific transcripts that become restricted to their corresponding precursors, following oriented and asymmetric divisions. Here, we identify the primed gene ring finger 149 related (Rnf149-r), which later becomes restricted to the heart progenitors, but appears to regulate pharyngeal muscle fate specification in the cardiopharyngeal lineage. CRISPR/Cas9-mediated loss of Rnf149-r function impairs atrial siphon muscle morphogenesis, and downregulates Tbx1/10 and Ebf, two key determinants of pharyngeal muscle fate, while upregulating heart-specific gene expression. These phenotypes are reminiscent of the loss of FGF/MAPK signaling in the cardiopharyngeal lineage, and an integrated analysis of lineage-specific bulk RNA-seq profiling of loss-of-function perturbations has identified a significant overlap between candidate FGF/MAPK and Rnf149-r target genes. However, functional interaction assays suggest that Rnf149-r does not directly modulate the activity of the FGF/MAPK/Ets1/2 pathway. Instead, we propose that Rnf149-r acts both in parallel to the FGF/MAPK signaling on shared targets, as well as on FGF/MAPK-independent targets through (a) separate pathway(s).

Proteomic Signatures of the Serological Response to Influenza Vaccination in a Large Human Cohort Study.

The serological response to the influenza virus vaccine is highly heterogeneous for reasons that are not entirely clear. While the impact of demographic factors such as age, body mass index (BMI), sex, prior vaccination and titer levels are known to impact seroconversion, they only explain a fraction of the response. To identify signatures of the vaccine response, we analyzed 273 protein levels from 138 serum samples of influenza vaccine recipients (2019-2020 season). We found that levels of proteins functioning in cholesterol transport were positively associated with seroconversion, likely linking to the known impact of BMI. When adjusting seroconversion for the demographic factors, we identified additional, unexpected signatures: proteins regulating actin cytoskeleton dynamics were significantly elevated in participants with high adjusted seroconversion. Viral strain specific analysis showed that this trend was largely driven by the H3N2 strain. Further, we identified complex associations between adjusted seroconversion and other factors: levels of proteins of the complement system associated positively with adjusted seroconversion in younger participants, while they were associated negatively in the older population. We observed the opposite trends for proteins of high density lipoprotein remodeling, transcription, and hemostasis. In sum, careful integrative modeling can extract new signatures of seroconversion from highly variable data that suggest links between the humoral response as well as immune cell communication and migration.

Conserved Epigenetic Regulatory Logic Infers Genes Governing Cell Identity.

Determining genes that orchestrate cell differentiation in development and disease remains a fundamental goal of cell biology. This study establishes a genome-wide metric based on the gene-repressive trimethylation of histone H3 at lysine 27 (H3K27me3) across hundreds of diverse cell types to identify genetic regulators of cell differentiation. We introduce a computational method, TRIAGE, which uses discordance between gene-repressive tendency and expression to identify genetic drivers of cell identity. We apply TRIAGE to millions of genome-wide single-cell transcriptomes, diverse omics platforms, and eukaryotic cells and tissue types. Using a wide range of data, we validate the performance of TRIAGE in identifying cell-type-specific regulatory factors across diverse species including human, mouse, boar, bird, fish, and tunicate. Using CRISPR gene editing, we use TRIAGE to experimentally validate RNF220 as a regulator of Ciona cardiopharyngeal development and SIX3 as required for differentiation of endoderm in human pluripotent stem cells. A record of this paper's transparent peer review process is included in the Supplemental Information.

Simple Method to Quantify Protein Abundances from 1000 Cells.

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

The conserved histone chaperone LIN-53 is required for normal lifespan and maintenance of muscle integrity in Caenorhabditis elegans.

Whether extension of lifespan provides an extended time without health deteriorations is an important issue for human aging. However, to which degree lifespan and aspects of healthspan regulation might be linked is not well understood. Chromatin factors could be involved in linking both aging aspects, as epigenetic mechanisms bridge regulation of different biological processes. The epigenetic factor LIN-53 (RBBP4/7) associates with different chromatin-regulating complexes to safeguard cell identities in Caenorhabditis elegans as well as mammals, and has a role in preventing memory loss and premature aging in humans. We show that LIN-53 interacts with the nucleosome remodeling and deacetylase (NuRD) complex in C. elegans muscles to ensure functional muscles during postembryonic development and in adults. While mutants for other NuRD members show a normal lifespan, animals lacking LIN-53 die early because LIN-53 depletion affects also the histone deacetylase complex Sin3, which is required for a normal lifespan. To determine why lin-53 and sin-3 mutants die early, we performed transcriptome and metabolomic analysis revealing that levels of the disaccharide trehalose are significantly decreased in both mutants. As trehalose is required for normal lifespan in C. elegans, lin-53 and sin-3 mutants could be rescued by either feeding with trehalose or increasing trehalose levels via the insulin/IGF1 signaling pathway. Overall, our findings suggest that LIN-53 is required for maintaining lifespan and muscle integrity through discrete chromatin regulatory mechanisms. Since both LIN-53 and its mammalian homologs safeguard cell identities, it is conceivable that its implication in lifespan regulation is also evolutionarily conserved.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis.

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.