Stem-loop-induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control.

Activating transcription factor 4 (ATF4) is a master transcriptional regulator of the integrated stress response, leading cells toward adaptation or death. ATF4's induction under stress was thought to be due to delayed translation reinitiation, where the reinitiation-permissive upstream open reading frame 1 (uORF1) plays a key role. Accumulating evidence challenging this mechanism as the sole source of ATF4 translation control prompted us to investigate additional regulatory routes. We identified a highly conserved stem-loop in the uORF2/ATF4 overlap, immediately preceded by a near-cognate CUG, which introduces another layer of regulation in the form of ribosome queuing. These elements explain how the inhibitory uORF2 can be translated under stress, confirming prior observations but contradicting the original regulatory model. We also identified two highly conserved, potentially modified adenines performing antagonistic roles. Finally, we demonstrated that the canonical ATF4 translation start site is substantially leaky scanned. Thus, ATF4's translational control is more complex than originally described, underpinning its key role in diverse biological processes.

Identification of molecular signatures defines the differential proteostasis response in induced spinal and cranial motor neurons.

Amyotrophic lateral sclerosis damages proteostasis, affecting spinal and upper motor neurons earlier than a subset of cranial motor neurons. To aid disease understanding, we exposed induced cranial and spinal motor neurons (iCrMNs and iSpMNs) to proteotoxic stress, under which iCrMNs showed superior survival, quantifying the transcriptome and proteome for >8,200 genes at 0, 12, and 36 h. Two-thirds of the proteome showed cell-type differences. iSpMN-enriched proteins related to DNA/RNA metabolism, and iCrMN-enriched proteins acted in the endoplasmic reticulum (ER)/ER chaperone complex, tRNA aminoacylation, mitochondria, and the plasma/synaptic membrane, suggesting that iCrMNs expressed higher levels of proteins supporting proteostasis and neuronal function. When investigating the increased proteasome levels in iCrMNs, we showed that the activity of the 26S proteasome, but not of the 20S proteasome, was higher in iCrMNs than in iSpMNs, even after a stress-induced decrease. We identified Ublcp1 as an iCrMN-specific regulator of the nuclear 26S activity.

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.

Patient Subtyping Analysis of Baseline Multi-omic Data Reveals Distinct Pre-immune States Predictive of Vaccination Responses.

Understanding the molecular mechanisms that underpin diverse vaccination responses is a critical step toward developing efficient vaccines. Molecular subtyping approaches can offer valuable insights into the heterogeneous nature of responses and aid in the design of more effective vaccines. In order to explore the molecular signatures associated with the vaccine response, we analyzed baseline transcriptomics data from paired samples of whole blood, proteomics and glycomics data from serum, and metabolomics data from urine, obtained from influenza vaccine recipients (2019-2020 season) prior to vaccination. After integrating the data using a network-based model, we performed a subtyping analysis. The integration of multiple data modalities from 62 samples resulted in five baseline molecular subtypes with distinct molecular signatures. These baseline subtypes differed in the expression of pre-existing adaptive or innate immunity signatures, which were linked to significant variation across subtypes in baseline immunoglobulin A (IgA) and hemagglutination inhibition (HAI) titer levels. It is worth noting that these significant differences persisted through day 28 post-vaccination, indicating the effect of initial immune state on vaccination response. These findings highlight the significance of interpersonal variation in baseline immune status as a crucial factor in determining vaccine response and efficacy. Ultimately, incorporating molecular profiling could enable personalized vaccine optimization.

Stem-loop induced ribosome queuing in the uORF2/ATF4 overlap fine-tunes stress-induced human ATF4 translational control.

ATF4 is a master transcriptional regulator of the integrated stress response leading cells towards adaptation or death. ATF4's induction under stress was thought to be mostly due to delayed translation reinitiation, where the reinitiation-permissive uORF1 plays a key role. Accumulating evidence challenging this mechanism as the sole source of ATF4 translation control prompted us to investigate additional regulatory routes. We identified a highly conserved stem-loop in the uORF2/ATF4 overlap, immediately preceded by a near-cognate CUG, which introduces another layer of regulation in the form of ribosome queuing. These elements explain how the inhibitory uORF2 can be translated under stress, confirming prior observations, but contradicting the original regulatory model. We also identified two highly conserved, potentially modified adenines performing antagonistic roles. Finally, we demonstrate that the canonical ATF4 translation start site is substantially leaky-scanned. Thus, ATF4's translational control is more complex than originally described underpinning its key role in diverse biological processes.

Fractionation of Native Protein Complexes from Mammalian Cells to Determine the Differential Proteasome Activity and Abundance.

Eukaryotic cells have different types of proteasomes that differ in size. The smallest proteolytically active particle is the 20S proteasome, which degrades damaged and oxidized proteins; the most common larger particle is the 26S proteasome, which degrades ubiquitylated proteins. The 26S proteasome is formed by a 20S particle capped with one or two regulatory particles, named 19S. While proteasome particles function in the cytoplasm, endoplasmic reticulum, and nucleus, our understanding of their abundance and activity in different cellular compartments is still limited. We provide a three-step protocol that first involves detergent-based fractionation of the cytoplasmic and nuclear compartments, maintaining the integrity and activity of proteasome complexes. Second, the protocol employs native gel separation of large multiprotein complexes in the fractions and a fluorescence-based in-gel quantitation of the activity and different proteasome particles. Finally, the protocol involves protein in-gel denaturation and transfer to a PVDF membrane. Western blotting then detects and quantifies the different proteasome particles. Therefore, the protocol allows for sensitive measurements of activity and abundance of individual proteasome particles from different cellular compartments. It has been optimized for motor neurons induced from mouse embryonic stem cells but can be applied to a variety of mammalian cell lines. Key features • Protocol for fractionation of active nuclear and cytoplasmic proteasome complexes. • Native electrophoresis and fluorescence-based in-gel activity assay, which allows the visualization and quantification of active complexes within the acrylamide gel matrix. • In-gel protein denaturation followed by transfer of complexes to PVDF membrane, which allows the analysis of complexes' abundance using antibodies.

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).

Re-mining serum proteomics data reveals extensive post-translational modifications upon Zika and dengue infection.

Zika virus (ZIKV) and dengue virus (DENV) are two closely related flaviviruses with similar symptoms. However, due to the implications of ZIKV infections for pregnancy outcomes, understanding differences in their molecular impact on the host is of high interest. Viral infections change the host proteome, including post-translational modifications. As modifications are diverse and of low abundance, they typically require additional sample processing which is not feasible for large cohort studies. Therefore, we tested the potential of next-generation proteomics data in its ability to prioritize specific modifications for later analysis. We re-mined published mass spectra from 122 serum samples from ZIKV and DENV patients for the presence of phosphorylated, methylated, oxidized, glycosylated/glycated, sulfated, and carboxylated peptides. We identified 246 modified peptides with significantly differential abundance in ZIKV and DENV patients. Amongst these, methionine-oxidized peptides from apolipoproteins and glycosylated peptides from immunoglobulin proteins were more abundant in ZIKV patient serum and generate hypotheses on the potential roles of the modification in the infection. The results demonstrate how data-independent acquisition techniques can help prioritize future analyses of peptide modifications.

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.

Meiotic DNA breaks activate a streamlined phospho-signaling response that largely avoids protein-level changes.

Meiotic cells introduce a numerous programmed DNA breaks into their genome to stimulate meiotic recombination and ensure controlled chromosome inheritance and fertility. A checkpoint network involving key kinases and phosphatases coordinates the repair of these DNA breaks, but the precise phosphorylation targets remain poorly understood. It is also unknown whether meiotic DNA breaks change gene expression akin to the canonical DNA-damage response. To address these questions, we analyzed the meiotic DNA break response in Saccharomyces cerevisiae using multiple systems-level approaches. We identified 332 DNA break-dependent phosphorylation sites, vastly expanding the number of known events during meiotic prophase. Less than half of these events occurred in recognition motifs for the known meiotic checkpoint kinases Mec1 (ATR), Tel1 (ATM), and Mek1 (CHK2), suggesting that additional kinases contribute to the meiotic DNA-break response. We detected a clear transcriptional program but detected only very few changes in protein levels. We attribute this dichotomy to a decrease in transcript levels after meiotic entry that dampens the effects of break-induced transcription sufficiently to cause only minimal changes in the meiotic proteome.

Extracellular matrix stiffness regulates degradation of MST2 via SCF ßTrCP.

The Hippo pathway plays central roles in relaying mechanical signals during development and tumorigenesis, but how the proteostasis of the Hippo kinase MST2 is regulated remains unknown. Here, we found that chemical inhibition of proteasomal proteolysis resulted in increased levels of MST2 in human breast epithelial cells. MST2 binds SCFßTrCP E3 ubiquitin ligase and silencing ßTrCP resulted in MST2 accumulation. Site-directed mutagenesis combined with computational molecular dynamics studies revealed that ßTrCP binds MST2 via a non-canonical degradation motif. Additionally, stiffer extracellular matrix, as well as hyperactivation of integrins resulted in enhanced MST2 degradation mediated by integrin-linked kinase (ILK) and actomyosin stress fibers. Our study uncovers the underlying biochemical mechanisms controlling MST2 degradation and underscores how alterations in the microenvironment rigidity regulate the proteostasis of a central Hippo pathway component.

Prevaccination Glycan Markers of Response to an Influenza Vaccine Implicate the Complement Pathway.

A key to improving vaccine design and vaccination strategy is to understand the mechanism behind the variation of vaccine response with host factors. Glycosylation, a critical modulator of immunity, has no clear role in determining vaccine responses. To gain insight into the association between glycosylation and vaccine-induced antibody levels, we profiled the pre- and postvaccination serum protein glycomes of 160 Caucasian adults receiving the FLUZONE influenza vaccine during the 2019-2020 influenza season using lectin microarray technology. We found that prevaccination levels of Lewis A antigen (Lea) are significantly higher in nonresponders than responders. Glycoproteomic analysis showed that Lea-bearing proteins are enriched in complement activation pathways, suggesting a potential role of glycosylation in tuning the activities of complement proteins, which may be implicated in mounting vaccine responses. In addition, we observed a postvaccination increase in sialyl Lewis X antigen (sLex) and a decrease in high mannose glycans among high responders, which were not observed in nonresponders. These data suggest that the immune system may actively modulate glycosylation as part of its effort to establish effective protection postvaccination.

New Views of Old Proteins: Clarifying the Enigmatic Proteome.

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

Evaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine.

The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.

Mapping phyllosphere microbiota interactions in planta to establish genotype-phenotype relationships.

Host-associated microbiomes harbour hundreds of bacterial species that co-occur, creating the opportunity for manifold bacteria-bacteria interactions, which in turn contribute to the overall community structure. The mechanisms that underlie this self-organization among bacteria remain largely elusive. Here, we studied bacterial interactions in the phyllosphere microbiota. We screened for microbial interactions in planta by adding 200 endogenous strains individually to a 15-member synthetic community and tracking changes in community composition upon colonization of the model plant Arabidopsis. Ninety percent of the identified interactions in planta were negative, and phylogenetically closely related strains elicited consistent effects on the synthetic community, providing support for trait conservation. Community changes could be largely explained by binary interactions; however, we also identified a higher-order interaction of more than two interacting strains. We further focused on a prominent interaction between two members of the Actinobacteria. In the presence of Aeromicrobium Leaf245, the population of Nocardioides Leaf374 was reduced by almost two orders of magnitude. We identified a potent antimicrobial peptidase in Aeromicrobium Leaf245, which resulted in Nocardioides Leaf374 lysis. A respective Leaf245 mutant strain was necessary and sufficient to restore Nocardioides colonization in planta, demonstrating that direct bacteria-bacteria interactions were responsible for the population shift originally observed. Our study highlights the power of synthetic community screening and uncovers a strong microbial interaction that occurs despite a spatially heterogeneous environment.

New horizons in the stormy sea of multimodal single-cell data integration.

While measurements of RNA expression have dominated the world of single-cell analyses, new single-cell techniques increasingly allow collection of different data modalities, measuring different molecules, structural connections, and intermolecular interactions. Integrating the resulting multimodal single-cell datasets is a new bioinformatics challenge. Equally important, it is a new experimental design challenge for the bench scientist, who is not only choosing from a myriad of techniques for each data modality but also faces new challenges in experimental design. The ultimate goal is to design, execute, and analyze multimodal single-cell experiments that are more than just descriptive but enable the learning of new causal and mechanistic biology. This objective requires strict consideration of the goals behind the analysis, which might range from mapping the heterogeneity of a cellular population to assembling system-wide causal networks that can further our understanding of cellular functions and eventually lead to models of tissues and organs. We review steps and challenges toward this goal. Single-cell transcriptomics is now a mature technology, and methods to measure proteins, lipids, small-molecule metabolites, and other molecular phenotypes at the single-cell level are rapidly developing. Integrating these single-cell readouts so that each cell has measurements of multiple types of data, e.g., transcriptomes, proteomes, and metabolomes, is expected to allow identification of highly specific cellular subpopulations and to provide the basis for inferring causal biological mechanisms.

Protective role of the Arabidopsis leaf microbiota against a bacterial pathogen.

The aerial parts of plants are host to taxonomically structured bacterial communities. Members of the core phyllosphere microbiota can protect Arabidopsis thaliana against foliar pathogens. However, whether plant protection is widespread and to what extent the modes of protection differ among phyllosphere microorganisms are not clear. Here, we present a systematic analysis of plant protection capabilities of the At-LSPHERE, which is a collection of >200 bacterial isolates from A. thaliana, against the bacterial pathogen Pseudomonas syringae pv. tomato DC3000. In total, 224 bacterial leaf isolates were individually assessed for plant protection in a gnotobiotic system. Protection against the pathogen varied, with ~10% of leaf microbiota strains providing full protection, ~10% showing intermediate levels of protection and the remaining ~80% not markedly reducing disease phenotypes upon infection. The most protective strains were distributed across different taxonomic groups. Synthetic community experiments revealed additive effects of strains but also that a single strain can confer full protection in a community context. We also identify different mechanisms that contribute to plant protection. Although pattern-triggered immunity coreceptor signalling is involved in protection by a subset of strains, other strains protected in the absence of functional plant immunity receptors BAK1 and BKK1. Using a comparative genomics approach combined with mutagenesis, we reveal that direct bacteria-pathogen interactions contribute to plant protection by Rhizobium Leaf202. This shows that a computational approach based on the data provided can be used to identify genes of the microbiota that are important for plant protection.