The utility of protein and mRNA correlation

Comparative proteomics analysis of the mouse mini-gut organoid: insights into markers of gluten challenge from celiac disease intestinal biopsies

Introduction

Organoid models enable three-dimensional representation of cellular systems, providing flexible and accessible research tools, and can highlight key biomolecules. Such models of the intestinal epithelium can provide significant knowledge for the study of celiac disease and provide an additional context for the nature of markers observed from patient biopsy data.

Methods

Using LC-MS/MS, the proteomes of the crypt and enterocyte-like states of a mouse mini-gut organoid model were measured. The data were further compared with published biopsy data by comparing the changes induced by gluten challenge after a gluten-free diet.

Results and discussion

These analyses identified 4,850 protein groups and revealed how 400 putative biomarkers of dietary challenge were differentially expressed in the organoid model. In addition to the extensive changes within the differentiated cells, the data reiterated the disruption of the crypt-villus axis after gluten challenge. The mass spectrometry data are available via ProteomeXchange with the identifier PXD025690.

Comparative proteomics of sugarcane smut fungus - Sporisorium scitamineum unravels dynamic proteomic alterations during the dimorphic transition

Life cycle of the dimorphic sugarcane smut fungi, Sporisorium scitamineum, involves recognition and mating of compatible saprophytic yeast-like haploid sporidia (MAT-1 and MAT-2) that upon fusion, develop into infective dikaryotic mycelia. Although the dimorphic transition is intrinsically linked with the pathogenicity and virulence of S. scitamineum, it has never been studied using a proteomic approach. In the present study, an iTRAQ-based comparative proteomic analysis of three distinct stages was carried out. The stages were: the dimorphic transition period - haploid sporidial stage (MAT-1 and MAT-2); the transition phase (24 h post co-culturing (hpc)) and the dikaryotic mycelial stage (48 hpc). Functional categorization of differentially abundant proteins showed that the most altered biological processes were energy production, primary metabolism, especially, carbohydrate, amino acid, fatty acid, followed by translation, post-translation and protein turnover. Several differentially abundant proteins (DAPs), especially in the dikaryotic mycelial stage were predicted as effectors. Taken together, key molecular mechanisms underpinning the dimorphic transition in S. scitamineum at the proteome level were highlighted. The catalogue of stage-specific and dimorphic transition-associated-proteins and potential effectors identified herein represents a list of potential candidates for defective mutant screening to elucidate their functional role in the dimorphic transition and pathogenicity in S. scitamineum. BIOLOGICAL SIGNIFICANCE: Being the first comparative proteomics analysis of S. scitamineum, this study comprehensively examined three pivotal life cycle stages of the pathogen: the non-pathogenic haploid phase, the transition phase, and the pathogenic dikaryotic mycelial stage. While previous studies have reported the sugarcane and S. scitamineum interactions, this study endeavored to specifically identify the proteins responsible for pathogenicity. By analyzing the proteomic alterations between the haploid and dikaryotic mycelial phases, the study revealed significant changes in metabolic pathway-associated proteins linked to energy production, notably oxidative phosphorylation, and the citrate cycle. Furthermore, this study successfully identified key metabolic pathways that undergo reprogramming during the transition from the non-pathogenic to the pathogenic stage. The study also deciphered the underlying mechanisms driving the morphological and physiological alterations crucial for the S. scitamineum virulence. By studying its life cycle stages, identifying the key metabolic pathways and stage-specific proteins, it provides unprecedented insights into the pathogenicity and potential avenues for intervention. As proteomics continues to advance, such studies pave the way for a deeper understanding of plant-pathogen interactions and the development of innovative strategies to mitigate the impact of devastating pathogens like S. scitamineum.

Multi-dataset Integration and Residual Connections Improve Proteome Prediction from Transcriptomes using Deep Learning

Proteomes are well known to poorly correlate with transcriptomes measured from the same sample. While connected, the complex processes that impact the relationships between transcript and protein quantities remains an open research topic. Many studies have attempted to predict proteomes from transcriptomes with limited success. Here we use publicly available data from the Clinical Proteomics Tumor Analysis Consortium to show that deep learning models designed by neural architecture search (NAS) achieve improved prediction accuracy of proteome quantities from transcriptomics. We find that this benefit is largely due to including a residual connection in the architecture that allows input information to be remembered near the end of the network. Finally, we explore which groups of transcripts are functionally important for protein prediction using model interpretation with SHAP.

Advancing immunotherapy for melanoma: the critical role of single-cell analysis in identifying predictive biomarkers

Melanoma, a malignant skin cancer arising from melanocytes, exhibits rapid metastasis and a high mortality rate, especially in advanced stages. Current treatment modalities, including surgery, radiation, and immunotherapy, offer limited success, with immunotherapy using immune checkpoint inhibitors (ICIs) being the most promising. However, the high mortality rate underscores the urgent need for robust, non-invasive biomarkers to predict patient response to adjuvant therapies. The immune microenvironment of melanoma comprises various immune cells, which influence tumor growth and immune response. Melanoma cells employ multiple mechanisms for immune escape, including defects in immune recognition and epithelial-mesenchymal transition (EMT), which collectively impact treatment efficacy. Single-cell analysis technologies, such as single-cell RNA sequencing (scRNA-seq), have revolutionized the understanding of tumor heterogeneity and immune microenvironment dynamics. These technologies facilitate the identification of rare cell populations, co-expression patterns, and regulatory networks, offering deep insights into tumor progression, immune response, and therapy resistance. In the realm of biomarker discovery for melanoma, single-cell analysis has demonstrated significant potential. It aids in uncovering cellular composition, gene profiles, and novel markers, thus advancing diagnosis, treatment, and prognosis. Additionally, tumor-associated antibodies and specific genetic and cellular markers identified through single-cell analysis hold promise as predictive biomarkers. Despite these advancements, challenges such as RNA-protein expression discrepancies and tumor heterogeneity persist, necessitating further research. Nonetheless, single-cell analysis remains a powerful tool in elucidating the mechanisms underlying therapy response and resistance, ultimately contributing to the development of personalized melanoma therapies and improved patient outcomes.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

Evaluation of proteome dynamics: Implications for statistical confidence in mass spectrometric determination

Single-cell proteomics is currently far less productive than other approaches. Still, the proteomic community is having trouble adapting to the limitation of having to examine fewer cells than they would like. Studies on a small number of cells should be carefully planned to maximize the chances of success in this situation. This study aims to determine how sample size and measurement speed (slope)/variation affect the accuracy of a protein proteome mass spectrometric determination. The determination accuracy was shown to increase, and the false positive rate was shown to decrease as the sample size increased from 7 to 100 cells and the measurement slope/variation (S/V) ratio increased from 1 to 6. Furthermore, it was discovered that the number of cells in the sample increased the accuracy of this estimate. Thus, for 100 cells, the measurement S/V ratio was typically estimated to be very close to the real-world value, with a standard deviation of 0.35. For sample sizes from 7 to 100 cells, this accuracy was seen when calculating the measurement S/V ratio. The findings can help researchers plan experiments for mass spectroscopic protein proteome determination and other research purposes.

Transcriptomic signatures across a critical sedimentation threshold in a major reef-building coral

Sedimentation is a major cause of global near-shore coral reef decline. Although the negative impacts of sedimentation on coral reef community composition have been well-documented, the effects of sedimentation on coral metabolism in situ have received comparatively little attention. Using transcriptomics, we identified gene expression patterns changing across a previously defined sedimentation threshold that was deemed critical due to changes in coral cover and community composition. We identified genes, pathways, and molecular processes associated with this transition that may allow corals, such as Porites lobata, to tolerate chronic, severe sedimentation and persist in turbid environments. Alternative energy generation pathways may help P. lobata maintain a persistent stress response to survive when the availability of light and oxygen is diminished. We found evidence for the expression of genes linked to increased environmental sensing and cellular communication that likely allow P. lobata to efficiently respond to sedimentation stress and associated pathogen challenges. Cell damage increases under stress; consequently, we found apoptosis pathways over-represented under severe sedimentation, a likely consequence of damaged cell removal to maintain colony integrity. The results presented here provide a framework for the response of P. lobata to sedimentation stress under field conditions. Testing this framework and its related hypotheses using multi-omics approaches can deepen our understanding of the metabolic plasticity and acclimation potential of corals to sedimentation and their resilience in turbid reef systems.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

Altered expression of kisspeptin, dynorphin, and related neuropeptides in polycystic ovary syndrome: A cross-sectional study

Background

Since kisspeptin (KISS1) in the hypothalamus is affected by the inhibitory effect of dynorphin, it raises questions about the controlled balance of these 2 neuropeptides in women with and without polycystic ovary syndrome (PCOS).

Objective

This study compares the expression levels of KISS1, dynorphin, neurokinin-B, leptin, and neuropeptide-Y in women with and without PCOS.

Materials and Methods

In this cross-sectional study, the peripheral blood samples of 20 women with PCOS and 20 women without PCOS who referred to Yamin Kencana Clinic, Cipto Mangunkusumo hospital, Jakarta, Indonesia were enrolled from August-December 2022. mRNA relative expression of genes related to the central factors associated with PCOS, such as leptin, neuropeptide-Y, KISS1, tachykinin-3, and prodynorphin (PDYN), in PCOS and non-PCOS populations were examined. Gene quantification was carried out by the quantitative polymerase chain reaction method.

Results

The KISS1/PDYN ratio was significantly higher in the PCOS group than in the control group (p = 0.02), and the PDYN was lower in the PCOS group than the control group (p < 0.001). Moreover, the positive correlation between KISS1 and the KISS1/PDYN ratio was significantly stronger in the PCOS group than in the control group (R = 0.93; p < 0.001 vs. R = 0.66, p < 0.001).

Conclusion

Our results suggest that an increased KISS1/PDYN ratio in PCOS women is related to diminished dynorphin expression. Low expression of the gene encoding dynorphin and a high KISS1/PDYN ratio is highly specific to PCOS.

A Ratiometric Catalog of Protein Isoform Shifts in the Cardiac Fetal Gene Program

The fetal genetic program orchestrates cardiac development and the re-expression of fetal genes is thought to underlie cardiac disease and adaptation. Here, a proteomics ratio test using mass spectrometry is applied to find protein isoforms with statistically significant usage differences in the fetal vs. postnatal mouse heart. Changes in isoform usage ratios are pervasive at the protein level, with 104 significant events observed, including 88 paralog-derived isoform switching events and 16 splicing-derived isoform switching events between fetal and postnatal hearts. The ratiometric proteomic comparisons rediscovered hallmark fetal gene signatures including a postnatal switch from fetal β (MYH7) toward ɑ (MYH6) myosin heavy chains and from slow skeletal muscle (TNNI1) toward cardiac (TNNI3) troponin I. Altered usages in metabolic proteins are prominent, including a platelet to muscle phosphofructokinase (PFKP - PFKM), enolase 1 to 3 (ENO1 - ENO3), and alternative splicing of pyruvate kinase M2 toward M1 (PKM2 - PKM1) isoforms in glycolysis. The data also revealed a parallel change in mitochondrial proteins in cardiac development, suggesting the shift toward aerobic respiration involves also a remodeling of the mitochondrial protein isoform proportion. Finally, a number of glycolytic protein isoforms revert toward their fetal forms in adult hearts under pathological cardiac hypertrophy, suggesting their functional roles in adaptive or maladaptive response, but this reversal is partial. In summary, this work presents a catalog of ratiometric protein markers of the fetal genetic program of the mouse heart, including previously unreported splice isoform markers.

Non-Coding RNAs: Regulators of Stress, Ageing, and Developmental Decisions in Yeast?

Cells must change their properties in order to adapt to a constantly changing environment. Most of the cellular sensing and regulatory mechanisms described so far are based on proteins that serve as sensors, signal transducers, and effectors of signalling pathways, resulting in altered cell physiology. In recent years, however, remarkable examples of the critical role of non-coding RNAs in some of these regulatory pathways have been described in various organisms. In this review, we focus on all classes of non-coding RNAs that play regulatory roles during stress response, starvation, and ageing in different yeast species as well as in structured yeast populations. Such regulation can occur, for example, by modulating the amount and functional state of tRNAs, rRNAs, or snRNAs that are directly involved in the processes of translation and splicing. In addition, long non-coding RNAs and microRNA-like molecules are bona fide regulators of the expression of their target genes. Non-coding RNAs thus represent an additional level of cellular regulation that is gradually being uncovered.

Utilizing high-resolution ribosome profiling for the global investigation of gene expression in Chlamydomonas

Ribosome profiling (Ribo-seq) is a powerful method for the deep analysis of translation mechanisms and regulatory circuits during gene expression. Extraction and sequencing of ribosome-protected fragments (RPFs) and parallel RNA-seq yields genome-wide insight into translational dynamics and post-transcriptional control of gene expression. Here, we provide details on the Ribo-seq method and the subsequent analysis with the unicellular model alga Chlamydomonas reinhardtii (Chlamydomonas) for generating high-resolution data covering more than 10 000 different transcripts. Detailed analysis of the ribosomal offsets on transcripts uncovers presumable transition states during translocation of elongating ribosomes within the 5' and 3' sections of transcripts and characteristics of eukaryotic translation termination, which are fundamentally distinct for chloroplast translation. In chloroplasts, a heterogeneous RPF size distribution along the coding sequence indicates specific regulatory phases during protein synthesis. For example, local accumulation of small RPFs correlates with local slowdown of psbA translation, possibly uncovering an uncharacterized regulatory step during PsbA/D1 synthesis. Further analyses of RPF distribution along specific cytosolic transcripts revealed characteristic patterns of translation elongation exemplified for the major light-harvesting complex proteins, LHCs. By providing high-quality datasets for all subcellular genomes and attaching our data to the Chlamydomonas reference genome, we aim to make ribosome profiles easily accessible for the broad research community. The data can be browsed without advanced bioinformatic background knowledge for translation output levels of specific genes and their splice variants and for monitoring genome annotation.

Integrative temporal multi-omics reveals uncoupling of transcriptome and proteome during human T cell activation

Engagement of the T cell receptor (TCR) triggers molecular reprogramming leading to the acquisition of specialized effector functions by CD4 helper and CD8 cytotoxic T cells. While transcription factors, chemokines, and cytokines are known drivers in this process, the temporal proteomic and transcriptomic changes that regulate different stages of human primary T cell activation remain to be elucidated. Here, we report an integrative temporal proteomic and transcriptomic analysis of primary human CD4 and CD8 T cells following ex vivo stimulation with anti-CD3/CD28 beads, which revealed major transcriptome-proteome uncoupling. The early activation phase in both CD4 and CD8 T cells was associated with transient downregulation of the mRNA transcripts and protein of the central glucose transport GLUT1. In the proliferation phase, CD4 and CD8 T cells became transcriptionally more divergent while their proteome became more similar. In addition to the kinetics of proteome-transcriptome correlation, this study unveils selective transcriptional and translational metabolic reprogramming governing CD4 and CD8 T cell responses to TCR stimulation. This temporal transcriptome/proteome map of human T cell activation provides a reference map exploitable for future discovery of biomarkers and candidates targeting T cell responses.

Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution

Tumor deconvolution enables the identification of diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold-standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA sequencing) rather than protein levels. Despite the popularity of gene expression datasets, protein levels often provide a more accurate view of rare cell types. To facilitate the use, development, and reproducibility of multiomic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic datasets. Decomprolute incorporates the large-scale multiomic datasets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. http://pnnl-compbio.github.io/decomprolute.

Apoptosis activation during Lagovirus europaeus/GI.2 infection in rabbits

Rabbit Haemorrhagic Disease (RHD) is a severe disease caused by Lagovirus europaeus/GI.1 and GI.2. Immunological processes such as apoptosis are important factors involved in the pathogenesis of Rabbit Haemorrhagic Disease (RHD). The process of programmed cell death has been quite well characterized in infection with GI.1 strains, but apoptosis in infection with GI.2 strains has not been widely studied. This is particularly important as several studies have shown that significant differences in the host immune response are observed during infection with different strains of Lagovirus europaeus. In this study, we analyzed the gene expression, protein levels and activity of key apoptotic cell death factors in the spleen, kidney, lung, and heart of rabbits. As a result, we showed that there is a significant increase in caspase-3, Bax, Bcl2 and Bax/Bcl2 mRNA gene expression ratio in organs of infected animals. Our results show also increased levels of cleaved caspase-3, caspase-6 and PARP. Moreover, significant activity of caspase-3 was also detected. Our results indicate that caspase-3, caspase-6 and genes coding Bcl2 family proteins play a key role in the apoptotic response in Lagovirus europaeus/GI.2 infection in organs that are not the target of virus replication.

TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

Codon optimization regulates IgG3 and IgM expression and glycosylation in N. benthamiana

Plants are being increasingly recognized for the production of complex human proteins, including monoclonal antibodies (mAbs). Various methods have been applied to boost recombinant expression, with DNA codon usage being an important approach. Here, we transiently expressed three complex human mAbs in Nicotiana benthamiana, namely one IgG3 and two IgM directed against SARS-CoV-2 as codon optimized(CO) and non-codon optimized (NCO) variants. qRT-PCR exhibited significantly increased mRNA levels of all CO variants compared to the non-codon optimized orthologues, in line with increased protein expression. Purified CO and NCO mAbs did not exhibit obvious biochemical differences, as determined by SDS-PAGE and antigen binding activities. By contrast, enhanced production selectively impacts on glycosite occupancy and N-glycan processing, with increased mannosidic structures. The results point to a careful monitoring of recombinant proteins upon enhancing expression. Especially if it comes to therapeutic application even subtle modifications might alter product efficacy or increase immunogenicity.

Partner-seeking and limbic dopamine system are enhanced following social loss in male prairie voles (Microtus ochrogaster)

Death of a loved one is recognized as one of life's greatest stresses, and 10%-20% of bereaved individuals will experience a complicated or prolonged grieving period that is characterized by intense yearning for the deceased. The monogamous prairie vole (Microtus ochrogaster) is a rodent species that forms pair bonds between breeding partners and has been used to study the neurobiology of social behaviors and isolation. Male prairie voles do not display distress after isolation from a familiar, same-sex conspecific; however, separation from a bonded female partner increases emotional, stress-related, and proximity-seeking behaviors. Here, we tested the investigatory response of male voles to partner odor during a period of social loss. We found that males who lost their partner spent significantly more time investigating partner odor but not non-partner social odor or food odor. Bachelor males and males in intact pairings did not respond uniquely to any odor. Furthermore, we examined dopamine (DA) receptor mRNA expression in the anterior insula cortex (aIC), nucleus accumbens (NAc), and anterior cingulate (ACC), regions with higher activation in grieving humans. While we found some effects of relationship type on DRD1 and DRD2 expression in some of these regions, loss of a high-quality opposite-sex relationship had a significant effect on DA receptor expression, with pair-bonded/loss males having higher expression in the aIC and ACC compared with pair-bonded/intact and nonbonded/loss males. Together, these data suggest that both relationship type and relationship quality affect reunion-seeking behavior and motivational neurocircuits following social loss of a bonded partner.

Proteogenomic data and resources for pan-cancer analysis

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma

Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.

An overview of human single-cell RNA sequencing studies in neurobiological disease

Neurobiological disorders are highly prevalent medical conditions that contribute to significant morbidity and mortality. Single-cell RNA sequencing (scRNA-seq) is a technique that measures gene expression in individual cells. In this review, we survey scRNA-seq studies of tissues from patients suffering from neurobiological disease. This includes postmortem human brains and organoids derived from peripheral cells. We highlight a range of conditions, including epilepsy, cognitive disorders, substance use disorders, and mood disorders. These findings provide new insights into neurobiological disease in multiple ways, including discovering novel cell types or subtypes involved in disease, proposing new pathophysiological mechanisms, uncovering novel drug targets, or identifying potential biomarkers. We discuss the quality of these findings and suggest potential future directions and areas open for additional research, including studies of non-cortical brain regions and additional conditions such as anxiety disorders, mood disorders, and sleeping disorders. We argue that additional scRNA-seq of tissues from patients suffering from neurobiological disease could advance our understanding and treatment of these conditions.

Spatiotemporal proteomic atlas of multiple brain regions across early fetal to neonatal stages in cynomolgus monkey

Fetal stages are critical periods for brain development. However, the protein molecular signature and dynamics of the human brain remain unclear due to sampling difficulty and ethical limitations. Non-human primates present similar developmental and neuropathological features to humans. This study constructed a spatiotemporal proteomic atlas of cynomolgus macaque brain development from early fetal to neonatal stages. Here we showed that (1) the variability across stages was greater than that among brain regions, and comparisons of cerebellum vs. cerebrum and cortical vs. subcortical regions revealed region-specific dynamics across early fetal to neonatal stages; (2) fluctuations in abundance of proteins associated with neural disease suggest the risk of nervous disorder at early fetal stages; (3) cross-species analysis (human, monkey, and mouse) and comparison between proteomic and transcriptomic data reveal the proteomic specificity and genes with mRNA/protein discrepancy. This study provides insight into fetal brain development in primates.

TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis

Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.

Effective extraction of polyribosomes exposes gene expression strategies in primary astrocytes

Regulation of mRNA translation in astrocytes gains a growing interest. However, until now, successful ribosome profiling of primary astrocytes has not been reported. Here, we optimized the standard 'polysome profiling' method and generated an effective protocol for polyribosome extraction, which enabled genome-wide assessment of mRNA translation dynamics along the process of astrocyte activation. Transcriptome (RNAseq) and translatome (Riboseq) data generated at 0, 24 and 48 h after cytokines treatment, revealed dynamic genome-wide changes in the expression level of ∼12 000 genes. The data clarify whether a change in protein synthesis rate results from a change in mRNA level or translation efficiency per se. It exhibit different expression strategies, based on changes in mRNA abundance and/or translation efficiency, which are specifically assigned to gene subsets depending on their function. Moreover, the study raises an important take-home message related to the possible presence of 'difficult to extract' polyribosome sub-groups, in all cell types, thus illuminating the impact of ribosomes extraction methodology on experiments addressing translation regulation.

Comparative protein analysis of two maize genotypes with contrasting tolerance to low temperature

BACKGROUND

Low temperature (LT) stress is one of the major environmental stress factors affecting the growth and yield of maize (Zea mays L.). Hence, it is important to unravel the molecular mechanisms behind LT stress tolerance to improve molecular breeding in LT tolerant genotypes. In the present study, two maize genotypes viz. Gurez local from Kashmir Himalaya and tropical grown GM6, were dissected for their LT stress response in terms of accumulation of differentially regulated proteins (DRPs). Leaf proteome analysis at three-leaf stage of maize seedlings subjected to LT stress of 6 °C for a total of 12 h duration was performed using two dimensional gel electrophoresis (2D-PAGE) followed by subsequent identification of the proteins involved.

RESULTS

After MALDI-TOF (Matrix-assisted laser desorption/ionization-time of flight) and bioinformatics analysis, 19 proteins were successfully identified in Gurez local, while as 10 proteins were found to get successful identification in GM6. The interesting observations from the present investigation is the identification of three novel proteins viz. threonine dehydratase biosynthetic chloroplastic, thylakoidal processing peptidase 1 chloroplastic, and nodulin-like protein, whose role in abiotic stress tolerance, in general, and LT stress, in particular, has not been reported so far. It is important to highlight here that most of LT responsive proteins including the three novel proteins were identified from Gurez local only, owing to its exceptional LT tolerance. From the protein profiles, obtained in both genotypes immediately after LT stress perception, it was inferred that stress responsive protein accumulation and their expression fashion help the Gurez local in seedling establishment and withstand unfavorable conditions as compared to GM6. This was inferred from the findings of pathway enrichment analysis like regulation of seed growth, timing of floral transition, lipid glycosylation, and aspartate family amino acid catabolic processes, besides other key stress defense mechanisms. However, in GM6, metabolic pathways enriched were found to be involved in more general processes including cell cycle DNA replication and regulation of phenylpropanoid metabolism. Furthermore, majority of the qRT-PCR results of the selected proteins demonstrated positive correlation between protein levels and transcript abundance, thereby strengthening our findings.

CONCLUSIONS

In conclusion, our findings reported majority of the identified proteins in Gurez local exhibiting up-regulated pattern under LT stress as compared to GM6. Furthermore, three novel proteins induced by LT stress were found in Gurez local, requiring further functional validation. Therefore, our results offer more insights for elucidating the molecular networks mediating LT stress tolerance in maize.

Relationships between neurotransmitter receptor densities and expression levels of their corresponding genes in the human hippocampus

Neurotransmitter receptors are key molecules in signal transmission, their alterations are associated with brain dysfunction. Relationships between receptors and their corresponding genes are poorly understood, especially in humans. We combined in vitro receptor autoradiography and RNA sequencing to quantify, in the same tissue samples (7 subjects), the densities of 14 receptors and expression levels of their corresponding 43 genes in the Cornu Ammonis (CA) and dentate gyrus (DG) of human hippocampus. Significant differences in receptor densities between both structures were found only for metabotropic receptors, whereas significant differences in RNA expression levels mostly pertained ionotropic receptors. Receptor fingerprints of CA and DG differ in shapes but have similar sizes; the opposite holds true for their "RNA fingerprints", which represent the expression levels of multiple genes in a single area. In addition, the correlation coefficients between receptor densities and corresponding gene expression levels vary widely and the mean correlation strength was weak-to-moderate. Our results suggest that receptor densities are not only controlled by corresponding RNA expression levels, but also by multiple regionally specific post-translational factors.

RNA-seq reveals that anti-obesity irisin and triiodothyronine (T3) hormones differentially affect the purinergic signaling transcriptomics in differentiated human adipocytes

The anti-obesity thyroid hormone, triiodothyronine (T3), and irisin, an exercise- and/or cold-induced myokine, stimulate thermogenesis and energy consumption while decreasing lipid accumulation. The involvement of ATP signaling in adipocyte cell function and obesity has attracted increasing attention, but the crosstalk between the purinergic signaling cascade and anti-obesity hormones lacks experimental evidence. In this study, we investigated the effects of T3 and irisin in the transcriptomics of membrane-bound purinoceptors, ectonucleotidase enzymes and nucleoside transporters participating in the purinergic signaling in cultured human adipocytes. The RNA-seq analysis revealed that differentiated adipocytes express high amounts of ADORA1, P2RY11, P2RY12, and P2RX6 gene transcripts, along with abundant levels of transcriptional products encoding to purine metabolizing enzymes (ENPP2, ENPP1, NT5E, ADA and ADK) and transporters (SLC29A1, SCL29A2). The transcriptomics of purinergic signaling markers changed in parallel to the upsurge of "browning" adipocyte markers, like UCP1 and P2RX5, after treatment with T3 and irisin. Upregulation of ADORA1, ADORA2A and P2RX4 gene transcription was obtained with irisin, whereas T3 preferentially upregulated NT5E, SLC29A2 and P2RY11 genes. Irisin was more powerful than T3 towards inhibition of the leptin gene transcription, the SCL29A1 gene encoding for the ENT1 transporter, the E-NPP2 (autotaxin) gene, and genes that encode for two ADP-sensitive P2Y receptors, P2RY1 and P2RY12. These findings indicate that anti-obesity irisin and T3 hormones differentially affect the purinergic signaling transcriptomics, which might point towards new directions for the treatment of obesity and related metabolic disorders that are worth to be pursued in future functional studies.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Cold-adapted amphipod species upon heat stress: Proteomic responses and their correlation with transcriptomic responses

The cellular heat shock response (HSR) comprises transcriptomic and proteomic reactions to thermal stress. It was here addressed, how the proteomic, together with the transcriptomic HSR, relate to the thermal sensitivities of three cold-adapted but differently thermo-sensitive freshwater amphipod species. The proteomes of thermosensitive Eulimnogammarus verrucosus and thermotolerant Eulimnogammarus cyaneus, both endemic to Lake Baikal, and of thermotolerant Holarctic Gammarus lacustris were investigated upon 24 h exposure to the species-specific 10 % lethal temperatures (LT10). Furthermore, correlations of heat stress induced changes in proteomes (this study) and transcriptomes (previous study with identical experimental design) were examined. Proteomes indicated that the HSR activated processes encompassed (i) proteostasis maintenance, (ii) maintenance of cell adhesion, (iii) oxygen transport, (iv) antioxidant response, and (v) regulation of protein synthesis. Thermo-sensitive E. verrucosus showed the most pronounced proteomic HSR and the lowest correlation of transcriptomic and proteomic HSRs. For proteins related to translation (ribosomal proteins, elongation factors), transcriptomic and proteomic changes were inconsistent: transcripts were downregulated in many cases, with levels of corresponding proteins remaining unchanged. In the Eulimnogammarus species, levels of hemocyanin protein but not transcript were increased upon heat stress, suggesting a HSR also directed to enhance oxygen transport. Thermosensitive E. verrucosus showed the most pronounced relocation of transcription/translation activity to proteostasis maintenance, which may indicate that the general species-specific stability of protein structure could be a fundamental determinant of thermotolerance. By combining transcriptomic and proteomic response data, this study provides a comprehensive picture of the cellular HSR components in the studied amphipods.

Digital detection of proteins

This paper reviews methods for detecting proteins based on molecular digitization, i.e., the isolation and detection of single protein molecules or singulated ensembles of protein molecules. The single molecule resolution of these methods has resulted in significant improvements in the sensitivity of immunoassays beyond what was possible using traditional "analog" methods: the sensitivity of some digital immunoassays approach those of methods for measuring nucleic acids, such as the polymerase chain reaction (PCR). The greater sensitivity of digital protein detection has resulted in immuno-diagnostics with high potential societal impact, e.g., the early diagnosis and therapeutic intervention of Alzheimer's Disease. In this review, we will first provide the motivation for developing digital protein detection methods given the limitations in the sensitivity of analog methods. We will describe the paradigm shift catalyzed by single molecule detection, and will describe in detail one digital approach - which we call digital bead assays (DBA) - based on the capture and labeling of proteins on beads, identifying "on" and "off" beads, and quantification using Poisson statistics. DBA based on the single molecule array (Simoa) technology have sensitivities down to attomolar concentrations, equating to ∼10 proteins in a 200 μL sample. We will describe the concept behind DBA, the different single molecule labels used, the ways of analyzing beads (imaging of arrays and flow), the binding reagents and substrates used, and integration of these technologies into fully automated and miniaturized systems. We provide an overview of emerging approaches to digital protein detection, including those based on digital detection of nucleic acids labels, single nanoparticle detection, measurements using nanopores, and methods that exploit the kinetics of single molecule binding. We outline the initial impact of digital protein detection on clinical measurements, highlighting the importance of customized assay development and translational clinical research. We highlight the use of DBA in the measurement of neurological protein biomarkers in blood, and how these higher sensitivity methods are changing the diagnosis and treatment of neurological diseases. We conclude by summarizing the status of digital protein detection and suggest how the lab-on-a-chip community might drive future innovations in this field.

Protein Misfolding and Aggregation in Proteinopathies: Causes, Mechanism and Cellular Response

Proteins are central to life functions. Alterations in the structure of proteins are reflected in their function. Misfolded proteins and their aggregates present a significant risk to the cell. Cells have a diverse but integrated network of protection mechanisms. Streams of misfolded proteins that cells are continuously exposed to must be continually monitored by an elaborated network of molecular chaperones and protein degradation factors to control and contain protein misfolding problems. Aggregation inhibition properties of small molecules such as polyphenols are important as they possess other beneficial properties such as antioxidative, anti-inflammatory, and pro-autophagic properties and help neuroprotection. A candidate with such desired features is important for any possible treatment development for protein aggregation diseases. There is a need to study the protein misfolding phenomenon so that we can treat some of the worst kinds of human ailments related to protein misfolding and aggregation.

Investigation of IL-35 and IL-39, New Members of the IL-12 Family, in Different Clinical Presentations of Brucellosis

Brucellosis is significantly influenced by the interactions between the causative Brucella bacteria and host immunity. Recently identified cytokines have been described for their immunomodulatory effects in numerous inflammatory, autoimmune and infectious diseases. Some of them are new members of cytokine superfamilies, including several members of the IL-12 superfamily (IL-35, IL-39). The major purpose of the present study was to investigate the role of these new immunomodulatory cytokines in Brucella infections. The levels of IL-35 and IL-39 in the serum of 40 acute and 40 chronic brucellosis patients and 40 healthy controls were measured by ELISA. The mRNA levels of IL-35 and IL-39 in PBMCs were detected by RT-qPCR. Both IL-35 and IL-39 serum concentrations were significantly higher in healthy control subjects than in brucellosis patients, and IL-35 and IL-39 serum levels of chronic brucellosis patients were higher than those of acute cases. It was also found that the expression of Ebi3/IL-12A (IL-35 genes) and Ebi3/IL-23A (IL-39 genes) was upregulated in chronic brucellosis patients compared to healthy controls. Moreover, the expression of the Ebi3/IL-12A and Ebi3/IL-23A genes was lower in patients with acute brucellosis than in patients with chronic brucellosis. Overall, this study showed that IL-35 and IL-39 are positively correlated in brucellosis and significantly decreased during the disease. Significantly lower levels of IL-35 and IL-39 in acute brucellosis than in chronic brucellosis and healthy controls suggest that these cytokines may play a key role in suppressing the immune response to brucellosis and its progression to chronicity.

Increased FOXJ1 protein expression is associated with improved overall survival in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis Consortium Study

BACKGROUND

Recently, we showed a >60% difference in 5-year survival for patients with tubo-ovarian high-grade serous carcinoma (HGSC) when stratified by a 101-gene mRNA expression prognostic signature. Given the varied patient outcomes, this study aimed to translate prognostic mRNA markers into protein expression assays by immunohistochemistry and validate their survival association in HGSC.

METHODS

Two prognostic genes, FOXJ1 and GMNN, were selected based on high-quality antibodies, correlation with protein expression and variation in immunohistochemical scores in a preliminary cohort (n = 134 and n = 80, respectively). Six thousand four hundred and thirty-four (FOXJ1) and 5470 (GMNN) formalin-fixed, paraffin-embedded ovarian neoplasms (4634 and 4185 HGSC, respectively) represented on tissue microarrays from the Ovarian Tumor Tissue Analysis consortium underwent immunohistochemical staining and scoring, then univariate and multivariate survival analysis.

RESULTS

Consistent with mRNA, FOXJ1 protein expression exhibited a linear, increasing association with improved overall survival in HGSC patients. Women with >50% expression had the most favourable outcomes (HR = 0.78, 95% CI 0.67-0.91, p < 0.0001). GMNN protein expression was not significantly associated with overall HSGC patient survival. However, HGSCs with >35% GMNN expression showed a trend for better outcomes, though this was not significant.

CONCLUSION

We provide foundational evidence for the prognostic value of FOXJ1 in HGSC, validating the prior mRNA-based prognostic association by immunohistochemistry.

Gap Junctions and Ageing

Gap junctions, comprising connexin proteins, create conduits directly coupling the cytoplasms of adjacent cells. Expressed in essentially all tissues, dynamic gap junction structures enable the exchange of small molecules including ions and second messengers, and are central to maintenance of homeostasis and synchronized excitability. With such diverse and critical roles throughout the body, it is unsurprising that alterations to gap junction and/or connexin expression and function underlie a broad array of age-related pathologies. From neurological dysfunction to cardiac arrhythmia and bone loss, it is hard to identify a human disease state that does not involve reduced, or in some cases inappropriate, intercellular communication to affect organ function. With a complex life cycle encompassing several key regulatory steps, pathological gap junction remodeling during ageing can arise from alterations in gene expression, translation, intracellular trafficking, and posttranslational modification of connexins. Connexin proteins are now known to "moonlight" and perform a variety of non-junctional functions in the cell, independent of gap junctions. Furthermore, connexin "hemichannels" on the cell surface can communicate with the extracellular space without ever coupling to an adjacent cell to form a gap junction channel. This chapter will focus primarily on gap junctions in ageing, but such non-junctional connexin functions will be referred to where appropriate and the full spectrum of connexin biology should be noted as potentially causative/contributing to some findings in connexin knockout animals, for example.

Functional high-throughput screen identifies microRNAs that promote butyrate-induced death in colorectal cancer cells

The gut fermentation product butyrate displays anti-cancer properties in the human proximal colon, including the ability to inhibit proliferation and induce apoptosis in colorectal cancer (CRC) cells. A natural histone deacetylase inhibitor (HDACi), butyrate can alter histone acetylation patterns in CRC cells, and thereby regulate global gene expression, including the non-coding transcriptome and microRNAs (miRNAs). Dysregulated miRNA expression affects CRC development and progression; however, the interplay between miRNA activity and butyrate response remains to be elucidated. A high-throughput functional screen was employed to identify miRNAs that can act as enhancers of the anti-cancer properties of butyrate. Validation studies confirmed that several miRNAs, including miR-125b, miR-181a, miR-593, and miR-1227, enhanced apoptosis, decreased proliferation, and promoted cell-cycle arrest in the presence of butyrate. Pathway analyses of predicted miRNA target genes highlighted their likely involvement in critical cancer-related growth pathways, including WNT and PI3K signaling. Several cancer-associated miRNA targets, including TRIM29, COX2, PIK3R3, CCND1, MET, EEF2K, DVL3, and NUP62 were synergistically regulated by the combination of cognate miRNAs and butyrate. Overall, this study has exposed the potential of miRNAs to act as enhancers of the anti-cancer effects of HDAC inhibition and identifies specific miRNAs that might be exploited for therapeutic benefit.

New models of Parkinson's like neuroinflammation in human microglia clone 3: Activation profiles induced by INF-γ plus high glucose and mitochondrial inhibitors

Microglia activation and neuroinflammation have been extensively studied in murine models of neurodegenerative diseases; however, to overcome the genetic differences between species, a human cell model of microglia able to recapitulate the activation profiles described in patients is needed. Here we developed human models of Parkinson's like neuroinflammation by using the human microglia clone 3 (HMC3) cells, whose activation profile in response to classic inflammatory stimuli has been controversial and reported only at mRNA levels so far. In fact, we showed the increased expression of the pro-inflammatory markers iNOS, Caspase 1, IL-1β, in response to IFN-γ plus high glucose, a non-specific disease stimulus that emphasized the dynamic polarization and heterogenicity of the microglial population. More specifically, we demonstrated the polarization of HMC3 cells through the upregulation of iNOS expression and nitrite production in response to the Parkinson's like stimuli, 6-hydroxidopamine (6-OHDA) and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), the latter depending on the NF-κB pathway. Furthermore, we identified inflammatory mediators that promote the pro-inflammatory activation of human microglia as function of different pathways that can simulate the phenotypic transition according to the stage of the pathology. In conclusion, we established and characterized different systems of HMC3 cells activation as in vitro models of Parkinson's like neuroinflammation.

Protein prediction models support widespread post-transcriptional regulation of protein abundance by interacting partners

Protein and mRNA levels correlate only moderately. The availability of proteogenomics data sets with protein and transcript measurements from matching samples is providing new opportunities to assess the degree to which protein levels in a system can be predicted from mRNA information. Here we examined the contributions of input features in protein abundance prediction models. Using large proteogenomics data from 8 cancer types within the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data set, we trained models to predict the abundance of over 13,000 proteins using matching transcriptome data from up to 958 tumor or normal adjacent tissue samples each, and compared predictive performances across algorithms, data set sizes, and input features. Over one-third of proteins (4,648) showed relatively poor predictability (elastic net r ≤ 0.3) from their cognate transcripts. Moreover, we found widespread occurrences where the abundance of a protein is considerably less well explained by its own cognate transcript level than that of one or more trans locus transcripts. The incorporation of additional trans-locus transcript abundance data as input features increasingly improved the ability to predict sample protein abundance. Transcripts that contribute to non-cognate protein abundance primarily involve those encoding known or predicted interaction partners of the protein of interest, including not only large multi-protein complexes as previously shown, but also small stable complexes in the proteome with only one or few stable interacting partners. Network analysis further shows a complex proteome-wide interdependency of protein abundance on the transcript levels of multiple interacting partners. The predictive model analysis here therefore supports that protein-protein interaction including in small protein complexes exert post-transcriptional influence on proteome compositions more broadly than previously recognized. Moreover, the results suggest mRNA and protein co-expression analysis may have utility for finding gene interactions and predicting expression changes in biological systems.

Expanding the prostate cancer cell line repertoire with ACRJ-PC28, an AR-negative neuroendocrine cell line derived from an African-Caribbean patient

Prostate cell lines from diverse backgrounds are important to addressing disparities in prostate cancer (PCa) incidence and mortality rates among Black men. ACRJ-PC28 was developed from a transrectal needle biopsy and established via inactivation of the CDKN2A locus and simultaneous expression of human telomerase. Characterization assays included growth curve analysis, immunoblots, IHC, 3D cultures, immunofluorescence imaging, confocal microscopy, flow cytometry, WGS, and RNA-Seq. ACRJ-PC28 has been passaged more than 40 times in vitro over 10 months with a doubling time of 45 hours. STR profiling confirmed the novelty and human origin of the cell line. RNA-Seq confirmed the expression of prostate specific genes alpha-methylacyl-CoA racemase (AMACR) and NKX3.1 and Neuroendocrine specific markers synaptophysin (SYP) and enolase 2 (ENO2) and IHC confirmed the presence of AMACR. Immunoblots indicated the cell line is of basal-luminal type; expresses p53 and pRB and is AR negative. WGS confirmed the absence of exonic mutations and the presence of intronic variants that appear to not affect function of AR, p53, and pRB. RNA-Seq data revealed numerous TP53 and RB1 mRNA splice variants and the lack of AR mRNA expression. This is consistent with retention of p53 function in response to DNA damage and pRB function in response to contact inhibition. Soft agar anchorage-independent analysis indicated that the cells are transformed, confirmed by principal component analysis (PCA) where ACRJ-PC28 cells cluster alongside other PCa tumor tissues, yet was distinct. The novel methodology described should advance prostate cell line development, addressing the disparity in PCa among Black men.

Identification of Novel Genes and Proteoforms in Angiostrongylus costaricensis through a Proteogenomic Approach

RNA sequencing (RNA-Seq) and mass-spectrometry-based proteomics data are often integrated in proteogenomic studies to assist in the prediction of eukaryote genome features, such as genes, splicing, single-nucleotide (SNVs), and single-amino-acid variants (SAAVs). Most genomes of parasite nematodes are draft versions that lack transcript- and protein-level information and whose gene annotations rely only on computational predictions. Angiostrongylus costaricensis is a roundworm species that causes an intestinal inflammatory disease, known as abdominal angiostrongyliasis (AA). Currently, there is no drug available that acts directly on this parasite, mostly due to the sparse understanding of its molecular characteristics. The available genome of A. costaricensis, specific to the Costa Rica strain, is a draft version that is not supported by transcript- or protein-level evidence. This study used RNA-Seq and MS/MS data to perform an in-depth annotation of the A. costaricensis genome. Our prediction improved the reference annotation with (a) novel coding and non-coding genes; (b) pieces of evidence of alternative splicing generating new proteoforms; and (c) a list of SNVs between the Brazilian (Crissiumal) and the Costa Rica strain. To the best of our knowledge, this is the first time that a multi-omics approach has been used to improve the genome annotation of A. costaricensis. We hope this improved genome annotation can assist in the future development of drugs, kits, and vaccines to treat, diagnose, and prevent AA caused by either the Brazil strain (Crissiumal) or the Costa Rica strain.

Proteome effects of genome-wide single gene perturbations

Protein abundance is controlled at the transcriptional, translational and post-translational levels, and its regulatory principles are starting to emerge. Investigating these principles requires large-scale proteomics data and cannot just be done with transcriptional outcomes that are commonly used as a proxy for protein abundance. Here, we determine proteome changes resulting from the individual knockout of 3308 nonessential genes in the yeast Schizosaccharomyces pombe. We use similarity clustering of global proteome changes to infer gene functionality that can be extended to other species, such as humans or baker's yeast. Furthermore, we analyze a selected set of deletion mutants by paired transcriptome and proteome measurements and show that upregulation of proteins under stable transcript expression utilizes optimal codons.

Experimental reproducibility limits the correlation between mRNA and protein abundances in tumor proteomic profiles

Large-scale studies of human proteomes have revealed only a moderate correlation between mRNA and protein abundances. It is unclear to what extent this moderate correlation reflects post-transcriptional regulation and to what extent it reflects measurement error. Here, by analyzing replicate profiles of tumors and cell lines, we show that there is considerable variation in the reproducibility of measurements of transcripts and proteins from individual genes. Proteins with more reproducible measurements tend to have a higher mRNA-protein correlation, suggesting that measurement reproducibility accounts for a substantial fraction of the unexplained variation between mRNA and protein abundances. The reproducibility of individual proteins is somewhat consistent across studies, and we exploit this to develop an aggregate reproducibility score that explains a substantial amount of the variation in mRNA-protein correlations across multiple studies. Finally, we show that pathways previously reported to have a higher-than-average mRNA-protein correlation may simply contain members that can be more reproducibly quantified.

Drought induces epitranscriptome and proteome changes in stem-differentiating xylem of Populus trichocarpa

Understanding gene expression and regulation requires insights into RNA transcription, processing, modification, and translation. However, the relationship between the epitranscriptome and the proteome under drought stress remains undetermined in poplar (Populus trichocarpa). In this study, we used Nanopore direct RNA sequencing and tandem mass tag-based proteomic analysis to examine epitranscriptomic and proteomic regulation induced by drought treatment in stem-differentiating xylem (SDX). Our results revealed a decreased full-length read ratio under drought treatment and, especially, a decreased association between transcriptome and proteome changes in response to drought. Epitranscriptome analysis of cellulose- and lignin-related genes revealed an increased N6-Methyladenosine (m6A) ratio, which was accompanied by decreased RNA abundance and translation, under drought stress. Interestingly, usage of the distal poly(A) site increased during drought stress. Finally, we found that transcripts of highly expressed genes tend to have shorter poly(A) tail length (PAL), and drought stress increased the percentage of transcripts with long PAL. These findings provide insights into the interplay among m6A, polyadenylation, PAL, and translation under drought stress in P. trichocarpa SDX.

Deletion of Mechanosensory β1-integrin From Bladder Smooth Muscle Results in Voiding Dysfunction and Tissue Remodeling

The bladder undergoes large shape changes as it fills and empties and experiences complex mechanical forces. These forces become abnormal in diseases of the lower urinary tract such as overactive bladder, neurogenic bladder, and urinary retention. As the primary mechanosensors linking the actin cytoskeleton to the extracellular matrix (ECM), integrins are likely to play vital roles in maintaining bladder smooth muscle (BSM) homeostasis. In a tamoxifen-inducible smooth muscle conditional knockout of β1-integrin, there was concomitant loss of α1- and α3-integrins from BSM and upregulation of αV- and β3-integrins. Masson's staining showed a reduction in smooth muscle with an increase in collagenous ECM. Functionally, mice exhibited a changing pattern of urination by voiding spot assay up to 8 wk after tamoxifen. By 8 wk, there was increased frequency with reductions in voided volume, consistent with overactivity. Cystometrograms confirmed that there was a significant reduction in intercontractile interval with reduced maximal bladder pressure. Muscle strip myography revealed a loss of contraction force in response to electrical field stimulation, that was entirely due to the loss of muscarinic contractility. Quantitative western blotting showed a loss of M3 receptor and no change in P2X1. qPCR on ECM and interstitial genes revealed loss of Ntpd2, a marker of an interstitial cell subpopulation; and an upregulation of S100A4, which is often associated with fibroblasts. Collectively, the data show that the loss of appropriate mechanosensation through integrins results in cellular and extracellular remodeling, and concomitant bladder dysfunction that resembles lower urinary tract symptoms seen in older people.

Diet triggers specific responses of hypothalamic astrocytes in time and region dependent manner

Hypothalamic astrocytes are particularly affected by energy-dense food consumption. How the anatomical location of these glial cells and their spatial molecular distribution in the arcuate nucleus of the hypothalamus (ARC) determine the cellular response to a high caloric diet remains unclear. In this study, we investigated their distinctive molecular responses following exposure to a high-fat high-sugar (HFHS) diet, specifically in the ARC. Using RNA sequencing and proteomics, we showed that astrocytes have a distinct transcriptomic and proteomic profile dependent on their anatomical location, with a major proteomic reprogramming in hypothalamic astrocytes. By ARC single-cell sequencing, we observed that a HFHS diet dictates time- and cell- specific transcriptomic responses, revealing that astrocytes have the most distinct regulatory pattern compared to other cell types. Lastly, we topographically and molecularly characterized astrocytes expressing glial fibrillary acidic protein and/or aldehyde dehydrogenase 1 family member L1 in the ARC, of which the abundance was significantly increased, as well as the alteration in their spatial and molecular profiles, with a HFHS diet. Together, our results provide a detailed multi-omics view on the spatial and temporal changes of astrocytes particularly in the ARC during different time points of adaptation to a high calorie diet.

Quantitative proteomics reveals protein dysregulation during T cell activation in multiple sclerosis patients compared to healthy controls

Background

Multiple sclerosis (MS) is an autoimmune, neurodegenerative disorder with a strong genetic component that acts in a complex interaction with environmental factors for disease development. CD4⁺ T cells are pivotal players in MS pathogenesis, where peripherally activated T cells migrate to the central nervous system leading to demyelination and axonal degeneration. Through a proteomic approach, we aim at identifying dysregulated pathways in activated T cells from MS patients as compared to healthy controls.

Methods

CD4⁺ T cells were purified from peripheral blood from MS patients and healthy controls by magnetic separation. Cells were left unstimulated or stimulated in vitro through the TCR and costimulatory CD28 receptor for 24 h prior to sampling. Electrospray liquid chromatography-tandem mass spectrometry was used to measure protein abundances.

Results

Upon T cell activation the abundance of 1801 proteins was changed. Among these proteins, we observed an enrichment of proteins expressed by MS-susceptibility genes. When comparing protein abundances in T cell samples from healthy controls and MS patients, 18 and 33 proteins were differentially expressed in unstimulated and stimulated CD4⁺ T cells, respectively. Moreover, 353 and 304 proteins were identified as proteins exclusively induced upon T cell activation in healthy controls and MS patients, respectively and dysregulation of the Nur77 pathway was observed only in samples from MS patients.

Conclusions

Our study highlights the importance of CD4⁺ T cell activation for MS, as proteins that change in abundance upon T cell activation are enriched for proteins encoded by MS susceptibility genes. The results provide evidence for proteomic disturbances in T cell activation in MS, and pinpoint to dysregulation of the Nur77 pathway, a biological pathway known to limit aberrant effector T cell responses.

Benchmarking imputation methods for network inference using a novel method of synthetic scRNA-seq data generation

Background

Single cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of modern biology providing an unprecedented global view on cellular diversity and heterogeneity. In particular, the structure of gene-gene expression correlation contains information on the underlying gene regulatory networks. However, interpretation of scRNA-seq data is challenging due to specific experimental error and biases that are unique to this kind of data including drop-out (or technical zeros).

Methods

To deal with this problem several methods for imputation of zeros for scRNA-seq have been developed. However, it is not clear how these processing steps affect inference of genetic networks from single cell data. Here, we introduce Biomodelling.jl, a tool for generation of synthetic scRNA-seq data using multiscale modelling of stochastic gene regulatory networks in growing and dividing cells.

Results

Our tool produces realistic transcription data with a known ground truth network topology that can be used to benchmark different approaches for gene regulatory network inference. Using this tool we investigate the impact of different imputation methods on the performance of several network inference algorithms.

Conclusions

Biomodelling.jl provides a versatile and useful tool for future development and benchmarking of network inference approaches using scRNA-seq data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04778-9

Proteomic Analysis of Hypothalamus and Pituitary Gland in Pre and Postpubertal Brahman Heifers

The hypothalamus and the pituitary gland are directly involved in the complex systemic changes that drive the onset of puberty in cattle. Here, we applied integrated bioinformatics to elucidate the critical proteins underlying puberty and uncover potential molecular mechanisms from the hypothalamus and pituitary gland of prepubertal (n = 6) and postpubertal (n = 6) cattle. Proteomic analysis in the hypothalamus and pituitary gland revealed 275 and 186 differentially abundant (DA) proteins, respectively (adjusted p-value < 0.01). The proteome profiles found herein were integrated with previously acquired transcriptome profiles. These transcriptomic studies used the same tissues harvested from the same heifers at pre- and post-puberty. This comparison detected a small number of matched transcripts and protein changes at puberty in each tissue, suggesting the need for multiple omics analyses for interpreting complex biological systems. In the hypothalamus, upregulated DA proteins at post-puberty were enriched in pathways related to puberty, including GnRH, calcium and oxytocin signalling pathways, whereas downregulated proteins were observed in the estrogen signalling pathway, axon guidance and GABAergic synapse. Additionally, this study revealed that ribosomal pathway proteins in the pituitary were involved in the pubertal development of mammals. The reported molecules and derived protein-protein networks are a starting point for future experimental approaches that might dissect with more detail the role of each molecule to provide new insights into the mechanisms of puberty onset in cattle.

Mechanosensors control skeletal muscle mass, molecular clocks, and metabolism

BACKGROUND

Skeletal muscles (SkM) are mechanosensitive, with mechanical unloading resulting in muscle-devastating conditions and altered metabolic properties. However, it remains unexplored whether these atrophic conditions affect SkM mechanosensors and molecular clocks, both crucial for their homeostasis and consequent physiological metabolism.

METHODS

We induced SkM atrophy through 14 days of hindlimb suspension (HS) in 10 male C57BL/6J mice and 10 controls (CTR). SkM histology, gene expressions and protein levels of mechanosensors, molecular clocks and metabolism-related players were examined in the m. Gastrocnemius and m. Soleus. Furthermore, we genetically reduced the expression of mechanosensors integrin-linked kinase (Ilk1) and kindlin-2 (Fermt2) in myogenic C2C12 cells and analyzed the gene expression of mechanosensors, clock components and metabolism-controlling genes.

RESULTS

Upon hindlimb suspension, gene expression levels of both core molecular clocks and mechanosensors were moderately upregulated in m. Gastrocnemius but strongly downregulated in m. Soleus. Upon unloading, metabolism- and protein biosynthesis-related genes were moderately upregulated in m. Gastrocnemius but downregulated in m. Soleus. Furthermore, we identified very strong correlations between mechanosensors, metabolism- and circadian clock-regulating genes. Finally, genetically induced downregulations of mechanosensors Ilk1 and Fermt2 caused a downregulated mechanosensor, molecular clock and metabolism-related gene expression in the C2C12 model.

CONCLUSIONS

Collectively, these data shed new lights on mechanisms that control muscle loss. Mechanosensors are identified to crucially control these processes, specifically through commanding molecular clock components and metabolism.