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Splicing varies across brain regions, but the single-cell resolution of regional variation is unclear. We present a single-cell investigation of differential isoform expression (DIE) between brain regions using single-cell long-read sequencing in mouse hippocampus and prefrontal cortex in 45 cell types at postnatal day 7 ( www.isoformAtlas.com ). Isoform tests for DIE show better performance than exon tests. We detect hundreds of DIE events traceable to cell types, often corresponding to functionally distinct protein isoforms. Mostly, one cell type is responsible for brain-region specific DIE. However, for fewer genes, multiple cell types influence DIE. Thus, regional identity can, although rarely, override cell-type specificity. Cell types indigenous to one anatomic structure display distinctive DIE, e.g. the choroid plexus epithelium manifests distinct transcription-start-site usage. Spatial transcriptomics and long-read sequencing yield a spatially resolved splicing map. Our methods quantify isoform expression with cell-type and spatial resolution and it contributes to further our understanding of how the brain integrates molecular and cellular complexity. Alternative RNA splicing varies across the brain. Its mapping at single cell resolution is unclear. Here, the authors provide a spatial and single-cell splicing atlas reporting brain region- and cell type-specific expression of different isoforms in the postnatal mouse brain.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org ) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease. A draft map of the human proteome is presented here, accounting for over 80% of the annotated protein-coding genes in humans; some novel protein-coding regions, including translated pseudogenes, non-coding RNAs and upstream open reading frames, are identified. Mapping the human proteome More than a decade after publication of the draft human genome sequence, there is no direct equivalent for the human proteome. But in this issue of Nature two groups present mass spectrometry-based analysis of human tissues, body fluids and cells mapping the large majority of the human proteome. Akhilesh Pandey and colleagues identified 17,294 protein-coding genes and provide evidence of tissue- and cell-restricted proteins through expression profiling. They highlight the importance of proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions. The data set is available on http://www.humanproteomemap.org . Bernhard Kuster and colleagues have assembled protein evidence for 18,097 genes in ProteomicsDB (available on https://www.proteomicsdb.org ) and highlight the utility of the data, for example the identification of hundreds of translated lincRNAs, drug-sensitivity markers and discovering the quantitative relationship between mRNA and protein levels in tissues. Elsewhere in this issue, Vivien Marx reports on a third major proteomics project, the antibody-based Human Protein Atlas programme ( http://www.proteinatlas.org/ ).

Current technological advancements in clinical and research settings have permitted a more intensive and comprehensive understanding of Alzheimer’s disease (AD). This development in knowledge regarding AD pathogenesis has been implemented to produce disease-modifying drugs. The potential for accessible and effective therapeutic methods has generated a need for detecting this neurodegenerative disorder during early stages of progression because such remedial effects are more profound when implemented during the initial, prolonged prodromal stages of pathogenesis. The aggregation of amyloid-β (Aβ) and tau isoforms are characteristic of AD; thus, they are considered core candidate biomarkers. However, research attempting to establish the reliability of Aβ and tau as biomarkers has culminated in an amalgamation of contradictory results and theories regarding the biomarker concentrations necessary for an accurate diagnosis. In this review, we consider the capabilities and limitations of fluid biomarkers collected from cerebrospinal fluid, blood, and oral, ocular, and olfactory secretions as diagnostic tools for AD, along with the impact of the integration of these biomarkers in clinical settings. Furthermore, the evolution of diagnostic criteria and novel research findings are discussed. This review is a summary and reflection of the ongoing concerted efforts to establish fluid biomarkers as a diagnostic tool and implement them in diagnostic procedures. Alzheimer’s disease: early diagnostic biomarkers in body fluids Markers from body fluids could help clinicians diagnose Alzheimer’s disease before cognitive decline appears. After numerous setbacks in treating advanced Alzheimer’s, researchers are eager to identify biological indicators that facilitate earlier disease detection and interception. A review by YoungSoo Kim and colleagues at Yonsei University in South Korea, explores the promise of ‘fluid biomarkers,’ which enables diagnosis using cerebrospinal fluid (CSF), blood, oral, ocular, and olfactory fluid samples. Shifts in CSF levels of amyloid beta and tau, two proteins central to Alzheimer’s pathology, can reliably monitor at-risk individuals. Although CSF collection is unpleasant for patients, it remains more promising than blood, where current data for candidate fluid biomarkers are relatively inconclusive. In this review, investigations to discover safer, cheaper, and more reliable diagnostic tools to shift treatment from alleviation to prevention are introduced.

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation. Synopsis This study analyzes the gene isoform‐specific relationships between mRNA variation and protein degradation and underscores the diversity of protein turnover control in steady‐state gene expression. An optimized experimental and bioinformatic workflow is developed to study protein turnover in high throughput by combining single‐shot Data independent acquisition mass spectrometry (DIA‐MS) and pulse‐chase SILAC labeling experiments. The genome‐wide, protein specific correlation between mRNA variation and protein degradation is a powerful measure of post‐translational control in determining protein variability. The correlation analysis reveals the diversity of protein turnover at various scales, ranging from specific biological processes and organelles to sub‐organelles and splicing isoforms. mRNA intron retention switching mostly impacts the corresponding protein abundance but not protein degradation. Graphical Abstract This study analyzes the gene isoform‐specific relationships between mRNA variation and protein degradation and underscores the diversity of protein turnover control in steady‐state gene expression.

Alström syndrome (AS) is characterised by metabolic deficits, retinal dystrophy, sensorineural hearing loss, dilated cardiomyopathy and multi-organ fibrosis. Elucidating the function of the mutated gene, ALMS1, is critical for the development of specific treatments and may uncover pathways relevant to a range of other disorders including common forms of obesity and type 2 diabetes. Interest in ALMS1 is heightened by the recent discovery of its involvement in neonatal cardiomyocyte cell cycle arrest, a process with potential relevance to regenerative medicine. ALMS1 encodes a ~ 0.5 megadalton protein that localises to the base of centrioles. Some studies have suggested a role for this protein in maintaining centriole-nucleated sensory organelles termed primary cilia, and AS is now considered to belong to the growing class of human genetic disorders linked to ciliary dysfunction (ciliopathies). However, mechanistic details are lacking, and recent studies have implicated ALMS1 in several processes including endosomal trafficking, actin organisation, maintenance of centrosome cohesion and transcription. In line with a more complex picture, multiple isoforms of the protein likely exist and non-centrosomal sites of localisation have been reported. This review outlines the evidence for both ciliary and extra-ciliary functions of ALMS1.

Intact proteins yield to proteomics Conventional 'bottom-up' proteomics, in which mass spectrometry is used to analyse peptide mixtures made by tryptic digestion of target proteins, is a powerful way of characterizing complex proteomes. However, the technique has limitations when considering different protein isoforms and combinations of post-translational modifications. The 'top-down' approach is generally thought to be impractical because of the limitations of mass spectrometry and difficulties with automation. A new top-down system presented here avoids these problems by using a four-dimensional separation system that achieves greater proteome coverage than conventional methods. A proof-of-principle experiment shows that the method is capable of identifying previously undetected isoforms and isoform-specific post-translational modifications caused by cellular senescence. A full description of the human proteome relies on the challenging task of detecting mature and changing forms of protein molecules in the body. Large-scale proteome analysis 1 has routinely involved digesting intact proteins followed by inferred protein identification using mass spectrometry 2 . This ‘bottom-up’ process affords a high number of identifications (not always unique to a single gene). However, complications arise from incomplete or ambiguous 2 characterization of alternative splice forms, diverse modifications (for example, acetylation and methylation) and endogenous protein cleavages, especially when combinations of these create complex patterns of intact protein isoforms and species 3 . ‘Top-down’ interrogation of whole proteins can overcome these problems for individual proteins 4 , 5 , but has not been achieved on a proteome scale owing to the lack of intact protein fractionation methods that are well integrated with tandem mass spectrometry. Here we show, using a new four-dimensional separation system, identification of 1,043 gene products from human cells that are dispersed into more than 3,000 protein species created by post-translational modification (PTM), RNA splicing and proteolysis. The overall system produced greater than 20-fold increases in both separation power and proteome coverage, enabling the identification of proteins up to 105 kDa and those with up to 11 transmembrane helices. Many previously undetected isoforms of endogenous human proteins were mapped, including changes in multiply modified species in response to accelerated cellular ageing (senescence) induced by DNA damage. Integrated with the latest version of the Swiss-Prot database 6 , the data provide precise correlations to individual genes and proof-of-concept for large-scale interrogation of whole protein molecules. The technology promises to improve the link between proteomics data and complex phenotypes in basic biology and disease research 7 .

Proteoforms are specific molecular forms of protein products arising from a single gene that possess different structures and different functions. Therefore, a single gene can produce a large repertoire of proteoforms by means of allelic variations (mutations, indels, SNPs), alternative splicing and other pre-translational mechanisms, post-translational modifications (PTMs), conformational dynamics, and functioning. Resulting proteoforms that have different sizes, alternative splicing patterns, sets of post-translational modifications, protein–protein interactions, and protein–ligand interactions, might dramatically increase the functionality of the encoded protein. Herein, we have interrogated the tumor suppressor PTEN for its proteoforms and find that this protein exists in multiple forms with distinct functions and sub-cellular localizations. Furthermore, the levels of each PTEN proteoform in a given cell may affect its biological function. Indeed, the paradigm of the continuum model of tumor suppression by PTEN can be better explained by the presence of a continuum of PTEN proteoforms, diversity, and levels of which are associated with pathological outcomes than simply by the different roles of mutations in the PTEN gene. Consequently, understanding the mechanisms underlying the dysregulation of PTEN proteoforms by several genomic and non-genomic mechanisms in cancer and other diseases is imperative. We have identified different PTEN proteoforms, which control various aspects of cellular function and grouped them into three categories of intrinsic, function-induced, and inducible proteoforms. A special emphasis is given to the inducible PTEN proteoforms that are produced due to alternative translational initiation. The novel finding that PTEN forms dimers with biological implications supports the notion that PTEN proteoform–proteoform interactions may play hitherto unknown roles in cellular homeostasis and in pathogenic settings, including cancer. These PTEN proteoforms with unique properties and functionalities offer potential novel therapeutic opportunities in the treatment of various cancers and other diseases.

To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene – so-called proteoforms – that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation data as well as to more typical protein abundance vs. sample data matrices, demonstrating the systematic detection of assembly- and tissue-specific proteoform groups, respectively, in either dataset. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets. Many proteins exist in various proteoforms but detecting these variants by bottom-up proteomics remains difficult. Here, the authors present a computational approach based on peptide correlation analysis to identify and characterize proteoforms from bottom-up proteomics data.

Abundant regulatory 14-3-3 proteins have an extremely wide interactome and coordinate multiple cellular events via interaction with specifically phosphorylated partner proteins. Notwithstanding the key role of 14-3-3/phosphotarget interactions in many physiological and pathological processes, they are dramatically underexplored. Here, we focused on the 14-3-3 interaction with human Tau protein associated with the development of several neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Among many known phosphorylation sites within Tau, protein kinase A (PKA) phosphorylates several key residues of Tau and induces its tight interaction with 14-3-3 proteins. However, the stoichiometry and mechanism of 14-3-3 interaction with phosphorylated Tau (pTau) are not clearly elucidated. In this work, we describe a simple bacterial co-expression system aimed to facilitate biochemical and structural studies on the 14-3-3/pTau interaction. We show that dual co-expression of human fetal Tau with PKA in Escherichia coli results in multisite Tau phosphorylation including also naturally occurring sites which were not previously considered in the context of 14-3-3 binding. Tau protein co-expressed with PKA displays tight functional interaction with 14-3-3 isoforms of a different type. Upon triple co-expression with 14-3-3 and PKA, Tau protein could be co-purified with 14-3-3 and demonstrates complex which is similar to that formed in vitro between individual 14-3-3 and pTau obtained from dual co-expression. Although used in this study for the specific case of the previously known 14-3-3/pTau interaction, our co-expression system may be useful to study of other selected 14-3-3/phosphotarget interactions and for validations of 14-3-3 complexes identified by other methods.

Targeted therapy and immunotherapy have revolutionized treatment of various cancers in the past decade. Despite targeted therapy with trastuzumab in Her2-positive gastric cancer patients, survival has been dismal, mostly due to disease progression and toxicity related to the treatments. One area of active development is looking for ideal monoclonal antibodies (IMAB) specific to the proteins only on the tumor and hence avoiding unnecessary side effects. Claudin proteins with isoform 2 are one such protein, specific for several cancers, particularly gastric cancer and its metastases, leading to the development of anti-claudin 18.2 specific antibody, claudiximab. This review will highlight the latest development of claudiximab as first in class IMAB for the treatment of gastric cancer.