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Multicellular organisms require carefully orchestrated communication between and within cell types and tissues, and many unicellular organisms also sense their context and environment, sometimes coordinating their responses. This review highlights contributions from chemical biology in discovering and probing mechanisms of cell-cell communication. We focus on chemical tools for labelling proteins in a cellular context and how these can be applied to decipher the target receptor of a signalling molecule, label a receptor of interest in situ to understand its biology, provide a read-out of protein activity or interactions in downstream signalling pathways, or discover protein-protein interactions across cell-cell interfaces., (© 2023 The Author(s).)

Proteins are essential biomacromolecules in all living systems because they are the prominent ultimate executives of the genetic information stored in DNA. Thus, studying protein is one of the central tasks in biological sciences. The complexity, diversity, and dynamics of a protein's structure, function, and structure-function relationship, the inherent structural fragility and thus the requirements on handling proteins to maintain protein's structural and functional orderliness make it a rather tricky task to work with protein. The approach to understanding the functions of a protein has been progressing steadily. In this paper, we reviewed the progress on the approach to the functional study of proteins that tremendously contributed to understanding their biological significance. Emphasis was put on the advances in the age in which high-throughput DNA sequencing and bioinformatics analysis are revolutionizing biological study., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

This paper, addressed to both philosophers of science and stem cell biologists, aims to reduce the obscurity of and disagreements over the nature of stemness. The two most prominent current theories of stemness--the entity theory and the state theory--are both biologically and philosophically unsatisfactory. Improved versions of these theories are likely to converge. Philosophers of science can perform a much needed service in clarifying and formulating ways of testing entity and state theories of stemness. To do so, however, philosophers should acquaint themselves with the latest techniques and approaches employed by bench scientists, such as the use of proteomics, genome-wide association studies, and ChIP-on-chip arrays. An overarching theme of this paper is the desirability of bringing closer together the philosophy of science and the practice of scientific research.

Nerve injury or dysfunction in the peripheral and central nervous systems are the leading causes for the development of neuropathies, which are frequently associated with allodynia and hyperalgesia. Treatment of these disorders is often unsatisfactory due to side effects or insufficient analgesia of the currently available drugs. Therefore, elucidating the molecular mechanisms of neuropathic pain is an important prerequisite for the rational development of novel analgesic drugs for the therapy of neuropathic pain. Several proteomic approaches have been performed to explore protein modifications in the nervous system associated with neuropathies in different animal models, which might contribute to the detection of new drug targets. Furthermore, there are proteomic studies investigating human cerebrospinal fluid from patients suffering from neuropathies. The results of these studies and the potential clinical value of the proteomic data are summarized and discussed in this review.

Drug discovery has been improved greatly by series of new ideas and new technologies as well as new approaches emerging in the postgenomic era. On the one hand, the theoretics of drug discovery become more comprehensive and more profound as the development of numerous new disciplines such as genomics, proteomics, transcriptomics, metabonomics, bioinformatics and system biology; on the other hand, the pathways for new drug discovery are broadened by the continuous improvement of technological platforms including computer-aided drug design, high throughput screening, high content screening, biochip, transgenic and RNAi technology. Based on the recent advances on the modern biology, in this article, we specially reviewed the impacts of modern biology on the process of drug discovery.

Systems biology is frequently defined as the study of all of the elements in a biological system and their relationship to one another in response to perturbation. Advances in science and technology are enabling the development of this emerging and cross-disciplinary field by allowing researchers to explore how biological components function as a network in cells, tissues and organisms. Recently, pharmaceutical companies have begun to embrace systems approaches in an effort to better understand physiology, pathogenic processes and pharmacological responses. This review focuses on recent advances within three core areas of systems biology: data collection, data analysis, and the integration and sharing of data.

Biological data from high-throughput technologies describing the network components (genes, proteins, metabolites) and their associated interactions have driven the reconstruction and study of structural (topological) properties of large-scale biological networks. In this article, we address the relation of the functional and structural properties by using extensively experimentally validated genome-scale metabolic network models to compute observable functional states of a microorganism and compare the "structure versus function" attributes of metabolic networks. It is observed that, functionally speaking, the essentiality of reactions in a node is not correlated with node connectivity as structural analyses of other biological networks have suggested. These findings are illustrated with the analysis of the genome-scale biochemical networks of three species with distinct modes of metabolism. These results also suggest fundamental differences among different biological networks arising out of their representation and functional constraints.

The scientific techniques used in molecular biological research and drug discovery have changed dramatically over the past 10 years due to the influence of genomics, proteomics and bioinformatics. Furthermore, genomics and functional genomics are now merging into a new scientific approach called chemogenomics. Advancements in the study of molecular cell biology are dependent upon "omics" researchers realizing the importance of and using the experimental tools currently available to cell biologists. For example, novel microscopic techniques utilizing advanced computer imaging allow for the examination of live specimens in a fourth dimension, viz., time. Yet, molecular biologists have not taken full advantage of these and other traditional and novel cell biology techniques for the further advancement of genomic and proteomic-oriented research. The application of traditional and novel cellular biological techniques will enhance the science of genomics. The authors hypothesize that a stronger interdisciplinary approach must be taken between cell biology (and its closely related fields) and genomics, proteomics and bio-chemoinformatics. Since there is a lot of confusion regarding many of the "omics" definitions, this article also clarifies some of the basic terminology used in genomics, and related fields. It also reviews the current status and future potential of chemogenomics and its relationship to cell biology. The authors also discuss and expand upon the differences between chemogenomics and the relatively new term--chemoproteomics. We conclude that the advances in cell biology methods and approaches and their adoption by "omics" researchers will allow scientists to maximize our knowledge about life.

Ribosomes are universally conserved cellular machines that catalyze protein biosynthesis. The active sites underly immense evolutionary conservation resulting in virtually identical core structures of ribosomes in all domains of life including organellar ribosomes. However, more peripheral structures of cytosolic ribosomes changed during evolution accommodating new functions and regulatory options. The expansion occurred at the riboprotein level, including more and larger ribosomal proteins and at the RNA level increasing the length of ribosomal RNA. Expansions within the ribosomal RNA occur as clusters at conserved sites that face toward the periphery of the cytosolic ribosome. Recent biochemical and structural work has shed light on how rRNA-specific expansion segments (ESs) recruit factors during translation and how they modulate translation dynamics in the cytosol. Here we focus on recent work on yeast, human and trypanosomal cytosolic ribosomes that explores the role of two specific rRNA ESs within the small and large subunit respectively. While no single regulatory strategy exists, the absence of ESs has consequences for proteomic stability and cellular fitness, rendering them fascinating evolutionary tools for tailored protein biosynthesis. [ABSTRACT FROM AUTHOR]

Causal discovery is a highly promising tool with a broad perspective in the field of biology. In this study, a causal structure robustness assessment algorithm is proposed and employed on the causal structures obtained, based on transcriptomic, proteomic, and the combined datasets, emerging from a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. 'Tragana Edessis' tissues. The algorithm assesses the impact of intervening in the datasets of the causal structures, using various criteria. The results showed that specific tissues exhibited an intense impact on the causal structures that were considered. In addition, the proteogenomic case demonstrated that biologically related tissues that referred to the same organ induced a similar impact on the causal structures considered, as was biologically expected. However, this result was subtler in both the transcriptomic and the proteomic cases. Furthermore, the causal structures based on a single omic analysis were found to be impacted to a larger extent, compared to the proteogenomic case, probably due to the distinctive biological features related to the proteome or the transcriptome. This study showcases the significance and perspective of assessing the causal structure robustness based on omic databases, in conjunction with causal discovery, and reveals advantages when employing a multiomics (proteogenomic) analysis compared to a single-omic (transcriptomic, proteomic) analysis. [ABSTRACT FROM AUTHOR]

Both lymph node metastases (LNMs) and tumour deposits (TDs) are included in colorectal cancer (CRC) staging, although knowledge regarding their biological background is lacking. This study aimed to compare the biology of these prognostic features, which is essential for a better understanding of their role in CRC spread. Spatially resolved transcriptomic analysis using digital spatial profiling was performed on TDs and LNMs from 10 CRC patients using 1,388 RNA targets, for the tumour cells and tumour microenvironment. Shotgun proteomics identified 5,578 proteins in 12 different patients. Differences in RNA and protein expression were analysed, and spatial deconvolution was performed. Image‐based consensus molecular subtype (imCMS) analysis was performed on all TDs and LNMs included in the study. Transcriptome and proteome profiles identified distinct clusters for TDs and LNMs in both the tumour and tumour microenvironment segment, with upregulation of matrix remodelling, cell adhesion/motility, and epithelial–mesenchymal transition (EMT) in TDs (all p < 0.05). Spatial deconvolution showed a significantly increased abundance of fibroblasts, macrophages, and regulatory T‐cells (p < 0.05) in TDs. Consistent with a higher fibroblast and EMT component, imCMS classified 62% of TDs as poor prognosis subtype CMS4 compared to 36% of LNMs (p < 0.05). Compared to LNMs, TDs have a more invasive state involving a distinct tumour microenvironment and upregulation of EMT, which are reflected in a more frequent histological classification of TDs as CMS4. These results emphasise the heterogeneity of locoregional spread and the fact that TDs should merit more attention both in future research and during staging. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot. [ABSTRACT FROM AUTHOR]

A milestone in the field of recombinant binding molecules was achieved 30 years ago with the discovery of single-domain antibodies from which antigen-binding variable domains, better known as nanobodies (Nbs), can be derived. Being only one tenth the size of conventional antibodies, Nbs feature high affinity and specificity, while being highly stable and soluble. In addition, they display accessibility to cryptic sites, low off-target accumulation and deep tissue penetration. Efficient selection methods, such as (semi-)synthetic/naïve or immunized cDNA libraries and display technologies, have facilitated the isolation of Nbs against diverse targets, and their single-gene format enables easy functionalization and high-yield production. This Review highlights recent advances in Nb applications in various areas of biological research, including structural biology, proteomics and high-resolution and in vivo imaging. In addition, we provide insights into intracellular applications of Nbs, such as live-cell imaging, biosensors and targeted protein degradation. [ABSTRACT FROM AUTHOR]

Submaximal exercise capacity is an indicator of cardiorespiratory fitness with clinical and public health implications. Submaximal exercise capacity and its response to exercise programs are characterized by heritability levels of about 40%. Using physical working capacity (power output) at a heart rate of 150 beats/min (PWC150) as an indicator of submaximal exercise capacity in subjects of the HERITAGE Family Study, we have undertaken multi-omics and in silico explorations of the underlying biology of PWC150 and its response to 20 wk of endurance training. Our goal was to illuminate the biological processes and identify panels of genes associated with human variability in intrinsic PWC150 (iPWC150) and its trainability (dPWC150). Our bioinformatics approach was based on a combination of genome-wide association, skeletal muscle gene expression, and plasma proteomics and metabolomics experiments. Genes, proteins, and metabolites showing significant associations with iPWC150 or dPWC150 were further queried for the enrichment of biological pathways. We compared genotype-phenotype associations of emerging candidate genes with reported functional consequences of gene knockouts in mouse models. We investigated the associations between DNA variants and multiple muscle and cardiovascular phenotypes measured in HERITAGE subjects. Two panels of prioritized genes of biological relevance to iPWC150 (13 genes) and dPWC150 (6 genes) were identified, supporting the hypothesis that genes and pathways associated with iPWC150 are different from those underlying dPWC150. Finally, the functions of these genes and pathways suggested that human variation in submaximal exercise capacity is mainly driven by skeletal muscle morphology and metabolism and red blood cell oxygen-carrying capacity. NEW & NOTEWORTHY Multi-omics and in silico explorations of the genes and underlying biology of submaximal exercise capacity and its response to 20 wk of endurance training were undertaken. Prioritized genes were identified: 13 genes for variation in submaximal exercise capacity in the sedentary state and 5 genes for the response level to endurance training, with no overlap between them. Genes and pathways associated with submaximal exercise capacity in the sedentary state are different from those underlying trainability. [ABSTRACT FROM AUTHOR]

Simple Summary: The accumulation of senescent cells is now widely known to be a driver of aging and many age-related pathologies, such as neurodegeneration and type 2 diabetes, among others. Targeting senescent cells for selective removal or altering the proteins they release are promising therapeutic strategies against age-related diseases. However, the biology of senescent cells is complex, dynamic, and heterogeneous. In order to better identify pathology-driving senescent cells and develop therapies to alter their complex biology or drive them toward cell death, a detailed and comprehensive understanding of senescence-associated proteins and the mechanisms that enable senescent cells to evade cell death is required. Major developments in proteomic workflows over the past decade have enabled an increasingly comprehensive, quantitative, and specific molecular profiling and interrogation of cellular mechanisms. In this review, we discuss the current state of translational senescence research and how modern proteomic technologies, particularly mass spectrometry-based proteomics, can accelerate our understanding of the fundamental mechanisms that drive senescence and robustly probe the proteomic phenotypes of heterogenous populations of senescent cells. We will focus on how these fundamental biological insights will ultimately accelerate the development of senescence-targeting therapies, or senotherapeutics. Cellular senescence is a state of irreversible growth arrest with profound phenotypic changes, including the senescence-associated secretory phenotype (SASP). Senescent cell accumulation contributes to aging and many pathologies including chronic inflammation, type 2 diabetes, cancer, and neurodegeneration. Targeted removal of senescent cells in preclinical models promotes health and longevity, suggesting that the selective elimination of senescent cells is a promising therapeutic approach for mitigating a myriad of age-related pathologies in humans. However, moving senescence-targeting drugs (senotherapeutics) into the clinic will require therapeutic targets and biomarkers, fueled by an improved understanding of the complex and dynamic biology of senescent cell populations and their molecular profiles, as well as the mechanisms underlying the emergence and maintenance of senescence cells and the SASP. Advances in mass spectrometry-based proteomic technologies and workflows have the potential to address these needs. Here, we review the state of translational senescence research and how proteomic approaches have added to our knowledge of senescence biology to date. Further, we lay out a roadmap from fundamental biological discovery to the clinical translation of senotherapeutic approaches through the development and application of emerging proteomic technologies, including targeted and untargeted proteomic approaches, bottom-up and top-down methods, stability proteomics, and surfaceomics. These technologies are integral for probing the cellular composition and dynamics of senescent cells and, ultimately, the development of senotype-specific biomarkers and senotherapeutics (senolytics and senomorphics). This review aims to highlight emerging areas and applications of proteomics that will aid in exploring new senescent cell biology and the future translation of senotherapeutics. [ABSTRACT FROM AUTHOR]

Context: Since most scientists tend to investigate live biological samples, there is inadequate data on efficient molecular techniques for the anthropological sciences. In this short review, multiple methods were mentioned and compared to provide a brief insight into the application of genomics and proteomics on the post-mortal specimen. Evidence Acquisition: Through the use of proper keywords, the PubMed and Elsevier databases were selected for acquiring relevant articles. Results: During cell death, DNA and proteins degenerate, hence, it is difficult to perform molecular assessments efficiently. Fortunately, with the aid of novel techniques, including uracil-N-glycosylase (UNG) and N-phenacylthiazolium bromide (PTB), we could partly recover the damaged DNA, and by applying PTB-DTT and Qiagen kit, we could analyze the remaining DNA with high efficiency. Nevertheless, there are countless gene sites for molecular studies, and the hypervariable region I (HVRI) of the D-loop in mitochondrial DNA (mtDNA) and Y chromosome microsatellites (Y-STRs) are two potential sites for anthropological studies. Finally, we could utilize proteomics in the remaining mineralization samples of a corpse to study protein variation and different phenotypes in human beings. Conclusions: Genomics and proteomics are two domains of molecular studies in which we can gather useful information about the events which occur in a cell over time. These domains give us data about the Archeological and Anthropological sciences. [ABSTRACT FROM AUTHOR]

Prototheca species are the only microalgae known to cause opportunistic infections in vertebrates and humans. Most cases of protothecosis in humans are caused by Prototheca wickerhamii, but knowledge of the pathogenicity and biology of Prototheca is limited. Globally, the diagnostic rate of Prototheca species infection is much lower than the actual rate of P. wickerhamii. The precise mechanisms underlying the pathogenesis of Prototheca infections remain unclear. In this study, we identified a strain of P. wickerhamii with atypical colony morphology. To reveal the morphological differences between P. wickerhamii S1 (mucous) and the molecular basis of its pathogenicity, the transcriptomics, proteomics, and metabolomics of two pathogenic P. wickerhamii strains and one environmental strain were analysed. Interestingly, mannan endo-1,4-b-mannosidase was significantly downregulated in P. wickerhamii S1, which contributes to a thinner cell wall in S1 compared to strains with typical colony morphology, and the toxicity of macrophages is reduced. Metabolite analysis revealed that the mucoid appearance of P. wickerhamii S1 may have been caused by an increase in linoleic acid, glycerol, and other metabolites. There is still a need to better understand the ecology, aetiology, and pathogenesis of P. wickerhamii, and in particular, its transmission between humans, animals, and the environment, from a One Health perspective. [ABSTRACT FROM AUTHOR]

Recent technological advances have opened the door to single-cell proteomics that can answer key biological questions regarding how protein expression, post-translational modifications, and protein interactions dictate cell state in health and disease. [ABSTRACT FROM AUTHOR]

Background: Identification and quantitation of newly synthesized proteins (NSPs) are critical to understanding protein dynamics in development and disease. Probing the nascent proteome can be achieved using non-canonical amino acids (ncAAs) to selectively label the NSPs utilizing endogenous translation machinery, which can then be quantitated with mass spectrometry. We have previously demonstrated that labeling the in vivo murine proteome is feasible via injection of azidohomoalanine (Aha), an ncAA and methionine (Met) analog, without the need for Met depletion. Aha labeling can address biological questions wherein temporal protein dynamics are significant. However, accessing this temporal resolution requires a more complete understanding of Aha distribution kinetics in tissues. Results: To address these gaps, we created a deterministic, compartmental model of the kinetic transport and incorporation of Aha in mice. Model results demonstrate the ability to predict Aha distribution and protein labeling in a variety of tissues and dosing paradigms. To establish the suitability of the method for in vivo studies, we investigated the impact of Aha administration on normal physiology by analyzing plasma and liver metabolomes following various Aha dosing regimens. We show that Aha administration induces minimal metabolic alterations in mice. Conclusions: Our results demonstrate that we can reproducibly predict protein labeling and that the administration of this analog does not significantly alter in vivo physiology over the course of our experimental study. We expect this model to be a useful tool to guide future experiments utilizing this technique to study proteomic responses to stimuli. [ABSTRACT FROM AUTHOR]

The skin is the outermost protective barrier of the human body. Its role is to protect against different physical, chemical, biological and environmental stressors. The vast majority of studies have focused on investigating the effects of single environmental stressors on skin homeostasis and the induction of several skin disorders, such as cancer or ageing. On the other hand, much fewer studies have explored the consequences of the co-exposure of skin cells to two or more stressors simultaneously, which is much more realistic. In the present study, we investigated, using mass-spectrometry-based proteomic analysis, the dysregulated biological functions in skin explants after their co-exposure to ultraviolet radiation (UV) and benzo[a]pyrene (BaP). We observed that several biological processes were dysregulated, among which autophagy appeared to be significantly downregulated. Furthermore, immunohistochemistry analysis was carried out to validate the downregulation of the autophagy process further. Altogether, the output of this study provides an insight into the biological responses of skin to combined exposure to UV + BaP and highlights autophagy as a potential target that might be considered in the future as a novel candidate for pharmacological intervention under such stress conditions. [ABSTRACT FROM AUTHOR]

Bacteria are ubiquitous lifeforms with important roles in the environment, biotechnology, and human health. Many of the functions that bacteria perform are mediated by proteins and enzymes, which catalyze metabolic transformations of small molecules and modifications of proteins. To better understand these biological processes, chemical proteomic approaches, including activity‐based protein profiling, have been developed to interrogate protein function and enzymatic activity in physiologically relevant contexts. Here, chemoproteomic strategies and technological advances for studying bacterial physiology, pathogenesis, and metabolism are discussed. The development of chemoproteomic approaches for characterizing protein function and enzymatic activity within bacteria remains an active area of research, and continued innovations are expected to provide breakthroughs in understanding bacterial biology. [ABSTRACT FROM AUTHOR]

The selection of plant genotypes with improved productivity and tolerance to environmental constraints has always been a major concern in plant breeding. Classical approaches based on the generation of variability and selection of better phenotypes from large variant collections have improved their efficacy and processivity due to the implementation of molecular biology techniques, particularly genomics, Next Generation Sequencing and other omics such as proteomics and metabolomics. In this regard, the identification of interesting variants before they develop the phenotype trait of interest with molecular markers has advanced the breeding process of new varieties. Moreover, the correlation of phenotype or biochemical traits with gene expression or protein abundance has boosted the identification of potential new regulators of the traits of interest, using a relatively low number of variants. These important breakthrough technologies, built on top of classical approaches, will be improved in the future by including the spatial variable, allowing the identification of gene(s) involved in key processes at the tissue and cell levels. [ABSTRACT FROM AUTHOR]

Background: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor prognosis. Proteogenomic characterization and integrative proteomic analysis provide a functional context to annotate genomic abnormalities with prognostic value. Methods: We performed an integrated multi-omics analysis, including whole-exome sequencing, RNA-seq, proteomic, and phosphoproteomic analysis of 217 PDAC tumors with paired non-tumor adjacent tissues. In vivo functional experiments were performed to further illustrate the biological events related to PDAC tumorigenesis and progression. Results: A comprehensive proteogenomic landscape revealed that TP53 mutations upregulated the CDK4-mediated cell proliferation process and led to poor prognosis in younger patients. Integrative multi-omics analysis illustrated the proteomic and phosphoproteomic alteration led by genomic alterations such as KRAS mutations and ADAM9 amplification of PDAC tumorigenesis. Proteogenomic analysis combined with in vivo experiments revealed that the higher amplification frequency of ADAM9 (8p11.22) could drive PDAC metastasis, though downregulating adhesion junction and upregulating WNT signaling pathway. Proteome-based stratification of PDAC revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Immune clustering defined a metabolic tumor subset that harbored FH amplicons led to better prognosis. Functional experiments revealed the role of FH in altering tumor glycolysis and in impacting PDAC tumor microenvironments. Experiments utilizing both in vivo and in vitro assay proved that loss of HOGA1 promoted the tumor growth via activating LARP7-CDK1 pathway. Conclusions: This proteogenomic dataset provided a valuable resource for researchers and clinicians seeking for better understanding and treatment of PDAC. [ABSTRACT FROM AUTHOR]

The poor prognosis of head and neck cancer (HNC) is associated with metastasis within the lymph nodes (LNs). Herein, the proteome of 140 multisite samples from a 59-HNC patient cohort, including primary and matched LN-negative or -positive tissues, saliva, and blood cells, reveals insights into the biology and potential metastasis biomarkers that may assist in clinical decision-making. Protein profiles are strictly associated with immune modulation across datasets, and this provides the basis for investigating immune markers associated with metastasis. The proteome of LN metastatic cells recapitulates the proteome of the primary tumor sites. Conversely, the LN microenvironment proteome highlights the candidate prognostic markers. By integrating prioritized peptide, protein, and transcript levels with machine learning models, we identify nodal metastasis signatures in blood and saliva. We present a proteomic characterization wiring multiple sites in HNC, thus providing a promising basis for understanding tumoral biology and identifying metastasis-associated signatures. The biological understanding of poor prognosis associated with lymph node metastasis in head and neck cancer (HNC) remains crucial. Here, a proteomic characterisation of 140 multisite samples from a 59-HNC patient cohort and machine learning reveals potential biomarkers and metastasis related signatures. [ABSTRACT FROM AUTHOR]

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: Blind mole rats (BMR) (Spalax, Nannospalax sp.) are extraordinary organisms with cancer resistance and a long lifespan for their size. Cellular senescence is a condition in which cells cease dividing irreversibly and secrete proinflammatory cytokines. To understand the mechanisms behind their superior traits, we utilized transcriptomics and proteomics tools in senescent BMR cells to compare them to similarly sized mice. The results revealed the alterations in Janus kinase (JAK) signaling and the cytokine-mediated pathway during the cellular senescence process in BMRs. These findings might reveal the novel mechanisms behind the unique biology of BMRs through cytokine-mediated adaptations. The blind mole rat (BMR), a long-living subterranean rodent, is an exceptional model for both aging and cancer research since they do not display age-related phenotypes or tumor formation. The Janus kinase–signal transducer and activator of transcription (JAK–STAT) signaling is a cytokine-stimulated pathway that has a crucial role in immune regulation, proliferation, and cytokine production. Therefore, the pathway has recently attracted interest in cellular senescence studies. Here, by using publicly available data, we report that JAK–STAT signaling was suppressed in the BMR in comparison to the mouse. Interestingly, our experimental results showed upregulated Jak1/2 expressions in BMR fibroblasts during the replicative senescence process. The transcriptomic analysis using publicly available data also demonstrated that various cytokines related to JAK–STAT signaling were upregulated in the late passage cells, while some other cytokines such as MMPs and SERPINs were downregulated, representing a possible balance of senescence-associated secretory phenotypes (SASPs) in the BMR. Finally, our proteomics data also confirmed cytokine-mediated signaling activation in senescent BMR fibroblasts. Together, our findings suggest the critical role of JAK–STAT and cytokine-mediated signaling pathways during cellular senescence, pointing to the possible contribution of divergent inflammatory factors to the superior resistance of aging and cancer in BMRs. [ABSTRACT FROM AUTHOR]

SUMMARY: Single‐cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high‐dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single‐cell omics, especially single‐cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well‐executed benchmarking studies to highlight advances made through the application of single‐cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single‐cell sequencing with revolutionary perspectives in plant biology. Significance Statement: In this review, we introduce the current technical advances in single‐cell omics, especially single‐cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well‐executed benchmarking studies to highlight advances made through the application of single‐cell omics techniques. [ABSTRACT FROM AUTHOR]

Background: Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results. Methods: Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes. Results: The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased. Conclusion: SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients. [ABSTRACT FROM AUTHOR]

Cross-linking and mass spectrometry (XL-MS) workflows represent an increasingly popular technique for low-resolution structural studies of macromolecular complexes. Cross-linking reactions take place in the solution state, capturing contact sites between components of a complex that represent the native, functionally relevant structure. Protein-protein XL-MS protocols are widely adopted, providing precise localization of cross-linking sites to single amino acid positions within a pair of cross-linked peptides. In contrast, protein-RNA XL-MS workflows are evolving rapidly and differ in their ability to localize interaction regions within the RNA sequence. Here, we review protein-protein and protein-RNA XL-MS workflows, and discuss their applications in studies of protein-RNA complexes. The examples highlight the complementary value of XL-MS in structural studies of protein-RNA complexes, where more established high-resolution techniques might be unable to produce conclusive data. [Display omitted] Sarnowski et al. review methods for the analysis of protein-RNA complexes by cross-linking mass spectrometry. Topics covered include protein-protein cross-linking in ribonucleoproteins for structural analysis; the identification of RNA-binding proteins; and the identification of specific RNA-interacting regions on proteins with and without the simultaneous identification of protein-binding sites on RNA. [ABSTRACT FROM AUTHOR]

Polyglutamylation is a posttranslational modification (PTM) that adds several glutamates on glutamate residues in the form of conjugated peptide chains by a family of enzymes known as polyglutamylases. Polyglutamylation is well documented in microtubules. Polyglutamylated microtubules consist of different α- and β-tubulin subunits with varied number of added glutamate residues. Kinetic control and catalytic rates of tubulin modification by polyglutamylases influence the polyglutamylation pattern of functional microtubules. The recent studies uncovered catalytic mechanisms of the glutamylation enzymes family, particularly tubulin tyrosine ligase-like (TTLL). Variable length polyglutamylation of primary sequence glutamyl residues have been mapped with a multitude of protein chemistry and proteomics approaches. Although polyglutamylation was initially considered a tubulin-specific modification, the recent studies have uncovered a calmodulin-dependent glutamylase, SidJ. Nano-electrospray ionization (ESI) proteomic approaches have identified quantifiable polyglutamylated sites in specific substrates. Indeed, conjugated glutamylated peptides were used in nano-liquid chromatography gradient delivery due to their relative hydrophobicity for their tandem mass spectrometry (MS/MS) characterization. The recent polyglutamylation characterization has revealed three major sites: E445 in α-tubulin, E435 in β-tubulin, and E860 in SdeA. In this review, we have summarized the progress made using proteomic approaches for large-scale detection of polyglutamylated peptides, including biology and analysis. [ABSTRACT FROM AUTHOR]