Defining the Human Brain Proteome Using Transcriptomics and Antibody-Based Profiling with a Focus on the Cerebral Cortex

Single-cell spatial transcriptomic atlas of the whole mouse brain

A comprehensive atlas of genes, cell types, and their spatial distribution across a whole mammalian brain is fundamental for understanding the function of the brain. Here, using single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq techniques, we generated a mouse brain atlas with spatial information for 308 cell clusters at single-cell resolution, involving over 4 million cells, as well as for 29,655 genes. We have identified cell clusters exhibiting preference for cortical subregions and explored their associations with brain-related diseases. Additionally, we pinpointed 155 genes with distinct regional expression patterns within the brainstem and unveiled 513 long non-coding RNAs showing region-enriched expression in the adult brain. Parcellation of brain regions based on spatial transcriptomic information revealed fine structure for several brain areas. Furthermore, we have uncovered 411 transcription factor regulons showing distinct spatiotemporal dynamics during neurodevelopment. Thus, we have constructed a single-cell-resolution spatial transcriptomic atlas of the mouse brain with genome-wide coverage.

Clinical studies of blood-borne Extracellular vesicles in psychiatry: A systematic review

Biomarkers for the diagnosis and clinical management of psychiatric disorders are currently lacking. Extracellular vesicles (EVs), lipid membrane-encapsulated vesicles released by cells, hold promise as a source of biomarkers due to their ability to carry molecules that reflect the status of their donor cells and their ubiquitous presence in biofluids. This review examines the literature on EVs in biofluids from psychiatric disorder patients, and discuss how the published studies contribute to our understanding of the pathophysiology of these conditions and to the discovery of potential biomarkers. We analyzed 46 studies on blood-borne EVs; no investigations on cerebrospinal fluid-derived EVs were found. A significant number of studies lacked optimal description of the methodology and/or characterization of the isolated EVs. Moreover, many studies aimed to capture brain-derived EVs, but often capture-proteins with low brain specificity were used. Considering biomarkers, miRNAs were the most investigated molecular type, but based on the studies analyzed it was not possible to identify robust biomarker candidates for the investigated disorders. Additionally, we describe the contribution of EV studies in illuminating the pathophysiology of psychiatric disorders, including research on insulin resistance, inflammation, mitochondrial dysfunction, and the microbiota. We conclude that there is a shortage of studies with detailed methodology description and EV sample characterization in psychiatric research. To exploit the potential of EVs to investigate psychiatric disorders and identify biomarkers more studies and validated protocols using capture proteins with high specificity to brain cells are needed. The review protocol was pre-registered in the PROSPERO database under the registration number CRD42021277534.

A Rare Case of Polymicrogyria in an Elderly Individual With Unique Polygenic Underlining

Polymicrogyria (PMG) is the most common malformation of cortical development (MCD) and presents as an irregularly patterned cortical surface with numerous small gyri and shallow sulci leading to various neurological deficits including developmental delays, intellectual disability, epilepsy, and language and motor issues. The presentation of PMG varies and is often found in conjunction with other congenital anomalies. Histologically, PMG features an abnormal cortical structure and dyslamination, resulting in its classification as a defect of neuronal migration and organization. Due in part to a variety of etiologies, little is known about the molecular mechanism(s) underlining PMG. To address this gap in knowledge, a case study is presented where an elderly individual with a medical history of unspecified PMG was examined postmortem by using a combination of anatomical, magnetic resonance imaging (MRI), histopathological, and genetic techniques. The results of the study allowed the classification of this case as bifrontal PMG. The genetic screening by whole exome sequencing (WES) on the Illumina Next Generation Sequencing (NGS) platform yielded 83 rare (minor allele frequency, MAF ≤ 0.01) pathological/deleterious variants where none of the respective genes has been previously linked to PMG. However, a subsequent analysis of those variants revealed that a significant number of affected genes were associated with most of the biological processes known to be impaired in PMG thereby pointing toward a polygenic nature in the present case. One of the notable features of the WES dataset was the presence of rare pathological/deleterious variants of genes (ADGRA2, PCDHA1, PCDHA12, PTK7, TPGS1, and USP4) involved in the regulation of Wnt signaling potentially highlighting the latter as an important PMG contributor in the present case. Notably, ADGRA2 warrants a closer look as a candidate gene for PMG because it not only regulates cortical patterning but has also been recently linked to two cases of bifrontal PMG with multiple congenital anomalies through its compound heterozygous mutations.

Evaluation of cerebrospinal fluid (CSF) and interstitial fluid (ISF) mouse proteomes for the validation and description of Alzheimer's disease biomarkers

BACKGROUND

Mass spectrometry (MS)-based cerebrospinal fluid (CSF) proteomics is an important method for discovering biomarkers of neurodegenerative diseases. CSF serves as a reservoir for interstitial fluid (ISF), and extensive communication between the two fluid compartments helps to remove waste products from the brain.

NEW METHOD

We performed proteomic analyses of both CSF and ISF fluid compartments using intracerebral microdialysis to validate and detect novel biomarkers of Alzheimer's disease (AD) in APPtg and C57Bl/6J control mice.

RESULTS

We identified up to 625 proteins in ISF and 4483 proteins in CSF samples. By comparing the biofluid profiles of APPtg and C57Bl/6J mice, we detected 37 and 108 significantly up- and downregulated candidates, respectively. In ISF, 7 highly regulated proteins, such as Gfap, Aldh1l1, Gstm1, and Txn, have already been implicated in AD progression, whereas in CSF, 9 out of 14 highly regulated proteins, such as Apba2, Syt12, Pgs1 and Vsnl1, have also been validated to be involved in AD pathogenesis. In addition, we also detected new interesting regulated proteins related to the control of synapses and neurotransmission (Kcna2, Cacng3, and Clcn6) whose roles as AD biomarkers should be further investigated.

COMPARISON WITH EXISTING METHODS

This newly established combined protocol provides better insight into the mutual communication between ISF and CSF as an analysis of tissue or CSF compartments alone.

CONCLUSIONS

The use of multiple fluid compartments, ISF and CSF, for the detection of their biological communication enables better detection of new promising AD biomarkers.

Enhanced In Situ Spatial Proteomics by Effective Combination of MALDI Imaging and LC-MS/MS

Highly specialized cells are fundamental for the proper functioning of complex organs. Variations in cell-type-specific gene expression and protein composition have been linked to a variety of diseases. Investigation of the distinctive molecular makeup of these cells within tissues is therefore critical in biomedical research. Although several technologies have emerged as valuable tools to address this cellular heterogeneity, most workflows lack sufficient in situ resolution and are associated with high costs and extremely long analysis times. Here, we present a combination of experimental and computational approaches that allows a more comprehensive investigation of molecular heterogeneity within tissues than by either shotgun LC-MS/MS or MALDI imaging alone. We applied our pipeline to the mouse brain, which contains a wide variety of cell types that not only perform unique functions but also exhibit varying sensitivities to insults. We explored the distinct neuronal populations within the hippocampus, a brain region crucial for learning and memory that is involved in various neurological disorders. As an example, we identified the groups of proteins distinguishing the neuronal populations of the dentate gyrus (DG) and the cornu ammonis (CA) in the same brain section. Most of the annotated proteins matched the regional enrichment of their transcripts, thereby validating the method. As the method is highly reproducible, the identification of individual masses through the combination of MALDI-IMS and LC-MS/MS methods can be used for the much faster and more precise interpretation of MALDI-IMS measurements only. This greatly speeds up spatial proteomic analyses and allows the detection of local protein variations within the same population of cells. The method's general applicability has the potential to be used to investigate different biological conditions and tissues and a much higher throughput than other techniques making it a promising approach for clinical routine applications.

HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations

We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm isotropic resolution for T1w, T2w, and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus are often impossible to identify using standard MRI protocols-can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with the existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high-quality individual brain. This serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical, and education settings.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Robust and rigorous identification of tissue-specific genes by statistically extending tau score

OBJECTIVES

In this study, we aimed to identify tissue-specific genes for various human tissues/organs more robustly and rigorously by extending the tau score algorithm.

INTRODUCTION

Tissue-specific genes are a class of genes whose functions and expressions are preferred in one or several tissues restrictedly. Identification of tissue-specific genes is essential for discovering multi-cellular biological processes such as tissue-specific molecular regulations, tissue development, physiology, and the pathogenesis of tissue-associated diseases.

MATERIALS AND METHODS

Gene expression data derived from five large RNA sequencing (RNA-seq) projects, spanning 96 different human tissues, were retrieved from ArrayExpress and ExpressionAtlas. The first step is categorizing genes using significant filters and tau score as a specificity index. After calculating tau for each gene in all datasets separately, statistical distance from the maximum expression level was estimated using a new meaningful procedure. Specific expression of a gene in one or several tissues was calculated after the integration of tau and statistical distance estimation, which is called as extended tau approach. Obtained tissue-specific genes for 96 different human tissues were functionally annotated, and some comparisons were carried out to show the effectiveness of the extended tau method.

RESULTS AND DISCUSSION

Categorization of genes based on expression level and identification of tissue-specific genes for a large number of tissues/organs were executed. Genes were successfully assigned to multiple tissues by generating the extended tau approach as opposed to the original tau score, which can assign tissue specificity to single tissue only.

Genome-wide annotation of protein-coding genes in pig

BACKGROUND

There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs.

RESULTS

An open-access pig expression map ( www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented.

CONCLUSIONS

Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource ( www.rnaatlas.org ), including a comparison to the expression of human orthologs.

The current state of glioma data registries

Background

The landscape of glioma research has evolved in the past 20 years to include numerous large, multi-institutional, database efforts compiling either clinical data on glioma patients, molecular data on glioma specimens, or a combination of both. While these strategies can provide a wealth of information for glioma research, obtaining information regarding data availability and access specifications can be challenging.

Methods

We reviewed the literature for ongoing clinical, molecular, and combined database efforts related to glioma research to provide researchers with a curated overview of the current state of glioma database resources.

Results

We identified and reviewed a total of 20 databases with data collection spanning from 1975 to 2022. Surveyed databases included both low- and high-grade gliomas, and data elements included over 100 clinical variables and 12 molecular data types. Select database strengths included large sample sizes and a wide variety of variables available, while limitations of some databases included complex data access requirements and a lack of glioma-specific variables.

Conclusions

This review highlights current databases and registries and their potential utility in clinical and genomic glioma research. While many high-quality resources exist, the fluid nature of glioma taxonomy makes it difficult to isolate a large cohort of patients with a pathologically confirmed diagnosis. Large, well-defined, and publicly available glioma datasets have the potential to expand the reach of glioma research and drive the field forward.

Microfluidic device with brain extracellular matrix promotes structural and functional maturation of human brain organoids

Brain organoids derived from human pluripotent stem cells provide a highly valuable in vitro model to recapitulate human brain development and neurological diseases. However, the current systems for brain organoid culture require further improvement for the reliable production of high-quality organoids. Here, we demonstrate two engineering elements to improve human brain organoid culture, (1) a human brain extracellular matrix to provide brain-specific cues and (2) a microfluidic device with periodic flow to improve the survival and reduce the variability of organoids. A three-dimensional culture modified with brain extracellular matrix significantly enhanced neurogenesis in developing brain organoids from human induced pluripotent stem cells. Cortical layer development, volumetric augmentation, and electrophysiological function of human brain organoids were further improved in a reproducible manner by dynamic culture in microfluidic chamber devices. Our engineering concept of reconstituting brain-mimetic microenvironments facilitates the development of a reliable culture platform for brain organoids, enabling effective modeling and drug development for human brain diseases.

Multi-cohort profiling reveals elevated CSF levels of brain-enriched proteins in Alzheimer's disease

OBJECTIVE

Decreased amyloid beta (Aβ) 42 together with increased tau and phospho-tau in cerebrospinal fluid (CSF) is indicative of Alzheimer's disease (AD). However, the molecular pathophysiology underlying the slowly progressive cognitive decline observed in AD is not fully understood and it is not known what other CSF biomarkers may be altered in early disease stages.

METHODS

We utilized an antibody-based suspension bead array to analyze levels of 216 proteins in CSF from AD patients, patients with mild cognitive impairment (MCI), and controls from two independent cohorts collected within the AETIONOMY consortium. Two additional cohorts from Sweden were used for biological verification.

RESULTS

Six proteins, amphiphysin (AMPH), aquaporin 4 (AQP4), cAMP-regulated phosphoprotein 21 (ARPP21), growth-associated protein 43 (GAP43), neurofilament medium polypeptide (NEFM), and synuclein beta (SNCB) were found at increased levels in CSF from AD patients compared with controls. Next, we used CSF levels of Aβ42 and tau for the stratification of the MCI patients and observed increased levels of AMPH, AQP4, ARPP21, GAP43, and SNCB in the MCI subgroups with abnormal tau levels compared with controls. Further characterization revealed strong to moderate correlations between these five proteins and tau concentrations.

INTERPRETATION

In conclusion, we report six extensively replicated candidate biomarkers with the potential to reflect disease development. Continued evaluation of these proteins will determine to what extent they can aid in the discrimination of MCI patients with and without an underlying AD etiology, and if they have the potential to contribute to a better understanding of the AD continuum.

The Impact of High Glucose or Insulin Exposure on S100B Protein Levels, Oxidative and Nitrosative Stress and DNA Damage in Neuron-Like Cells

Alzheimer’s disease (AD) is attracting considerable interest due to its increasing number of cases as a consequence of the aging of the global population. The mainstream concept of AD neuropathology based on pathological changes of amyloid β metabolism and the formation of neurofibrillary tangles is under criticism due to the failure of Aβ-targeting drug trials. Recent findings have shown that AD is a highly complex disease involving a broad range of clinical manifestations as well as cellular and biochemical disturbances. The past decade has seen a renewed importance of metabolic disturbances in disease-relevant early pathology with challenging areas in establishing the role of local micro-fluctuations in glucose concentrations and the impact of insulin on neuronal function. The role of the S100 protein family in this interplay remains unclear and is the aim of this research. Intracellularly the S100B protein has a protective effect on neurons against the toxic effects of glutamate and stimulates neurites outgrowth and neuronal survival. At high concentrations, it can induce apoptosis. The aim of our study was to extend current knowledge of the possible impact of hyper-glycemia and -insulinemia directly on neuronal S100B secretion and comparison to oxidative stress markers such as ROS, NO and DBSs levels. In this paper, we have shown that S100B secretion decreases in neurons cultured in a high-glucose or high-insulin medium, while levels in cell lysates are increased with statistical significance. Our findings demonstrate the strong toxic impact of energetic disturbances on neuronal metabolism and the potential neuroprotective role of S100B protein.

Fluid proteomics of CSF and serum reveal important neuroinflammatory proteins in blood-brain barrier disruption and outcome prediction following severe traumatic brain injury: a prospective, observational study

BACKGROUND

Severe traumatic brain injury (TBI) is associated with blood-brain barrier (BBB) disruption and a subsequent neuroinflammatory process. We aimed to perform a multiplex screening of brain enriched and inflammatory proteins in blood and cerebrospinal fluid (CSF) in order to study their role in BBB disruption, neuroinflammation and long-term functional outcome in TBI patients and healthy controls.

METHODS

We conducted a prospective, observational study on 90 severe TBI patients and 15 control subjects. Clinical outcome data, Glasgow Outcome Score, was collected after 6-12 months. We utilized a suspension bead antibody array analyzed on a FlexMap 3D Luminex platform to characterize 177 unique proteins in matched CSF and serum samples. In addition, we assessed BBB disruption using the CSF-serum albumin quotient (QA), and performed Apolipoprotein E-genotyping as the latter has been linked to BBB function in the absence of trauma. We employed pathway-, cluster-, and proportional odds regression analyses. Key findings were validated in blood samples from an independent TBI cohort.

RESULTS

TBI patients had an upregulation of structural CNS and neuroinflammatory pathways in both CSF and serum. In total, 114 proteins correlated with QA, among which the top-correlated proteins were complement proteins. A cluster analysis revealed protein levels to be strongly associated with BBB integrity, but not carriage of the Apolipoprotein E4-variant. Among cluster-derived proteins, innate immune pathways were upregulated. Forty unique proteins emanated as novel independent predictors of clinical outcome, that individually explained ~ 10% additional model variance. Among proteins significantly different between TBI patients with intact or disrupted BBB, complement C9 in CSF (p = 0.014, ΔR2 = 7.4%) and complement factor B in serum (p = 0.003, ΔR2 = 9.2%) were independent outcome predictors also following step-down modelling.

CONCLUSIONS

This represents the largest concomitant CSF and serum proteomic profiling study so far reported in TBI, providing substantial support to the notion that neuroinflammatory markers, including complement activation, predicts BBB disruption and long-term outcome. Individual proteins identified here could potentially serve to refine current biomarker modelling or represent novel treatment targets in severe TBI.

The Human Protein Atlas-Spatial localization of the human proteome in health and disease

For a complete understanding of a system's processes and each protein's role in health and disease, it is essential to study protein expression with a spatial resolution, as the exact location of proteins at tissue, cellular, or subcellular levels is tightly linked to protein function. The Human Protein Atlas (HPA) project is a large-scale initiative aiming at mapping the entire human proteome using antibody-based proteomics and integration of various other omics technologies. The publicly available knowledge resource www.proteinatlas.org is one of the world's most visited biological databases and has been extensively updated during the last few years. The current version is divided into six main sections, each focusing on particular aspects of the human proteome: (a) the Tissue Atlas showing the distribution of proteins across all major tissues and organs in the human body; (b) the Cell Atlas showing the subcellular localization of proteins in single cells; (c) the Pathology Atlas showing the impact of protein levels on survival of patients with cancer; (d) the Blood Atlas showing the expression profiles of blood cells and actively secreted proteins; (e) the Brain Atlas showing the distribution of proteins in human, mouse, and pig brain; and (f) the Metabolic Atlas showing the involvement of proteins in human metabolism. The HPA constitutes an important resource for further understanding of human biology, and the publicly available datasets hold much promise for integration with other emerging efforts focusing on single cell analyses, both at transcriptomic and proteomic level.

Rare Genetic Diseases: Nature's Experiments on Human Development

Rare genetic diseases are the result of a continuous forward genetic screen that nature is conducting on humans. Here, we present epistemological and systems biology arguments highlighting the importance of studying these rare genetic diseases. We contend that the expanding catalog of mutations in ∼4,000 genes, which cause ∼6,500 diseases and their annotated phenotypes, offer a wide landscape for discovering fundamental mechanisms required for human development and involved in common diseases. Rare afflictions disproportionately affect the nervous system in children, but paradoxically, the majority of these disease-causing genes are evolutionarily ancient and ubiquitously expressed in human tissues. We propose that the biased prevalence of childhood rare diseases affecting nervous tissue results from the topological complexity of the protein interaction networks formed by ubiquitous and ancient proteins encoded by childhood disease genes. Finally, we illustrate these principles discussing Menkes disease, an example of the discovery power afforded by rare diseases.

An atlas of the protein-coding genes in the human, pig, and mouse brain

The brain, with its diverse physiology and intricate cellular organization, is the most complex organ of the mammalian body. To expand our basic understanding of the neurobiology of the brain and its diseases, we performed a comprehensive molecular dissection of 10 major brain regions and multiple subregions using a variety of transcriptomics methods and antibody-based mapping. This analysis was carried out in the human, pig, and mouse brain to allow the identification of regional expression profiles, as well as to study similarities and differences in expression levels between the three species. The resulting data have been made available in an open-access Brain Atlas resource, part of the Human Protein Atlas, to allow exploration and comparison of the expression of individual protein-coding genes in various parts of the mammalian brain.

Using the Gibbs Function as a Measure of Human Brain Development Trends from Fetal Stage to Advanced Age

We propose to use a Gibbs free energy function as a measure of the human brain development. We adopt this approach to the development of the human brain over the human lifespan: from a prenatal stage to advanced age. We used proteomic expression data with the Gibbs free energy to quantify human brain’s protein–protein interaction networks. The data, obtained from BioGRID, comprised tissue samples from the 16 main brain areas, at different ages, of 57 post-mortem human brains. We found a consistent functional dependence of the Gibbs free energies on age for most of the areas and both sexes. A significant upward trend in the Gibbs function was found during the fetal stages, which is followed by a sharp drop at birth with a subsequent period of relative stability and a final upward trend toward advanced age. We interpret these data in terms of structure formation followed by its stabilization and eventual deterioration. Furthermore, gender data analysis has uncovered the existence of functional differences, showing male Gibbs function values lower than female at prenatal and neonatal ages, which become higher at ages 8 to 40 and finally converging at late adulthood with the corresponding female Gibbs functions.

Distinct Genetic Signatures of Cortical and Subcortical Regions Associated with Human Memory

Despite the discovery of gene variants linked to memory performance, understanding the genetic basis of adult human memory remains a challenge. Here, we devised an unsupervised framework that relies on spatial correlations between human transcriptome data and functional neuroimaging maps to uncover the genetic signatures of memory in functionally-defined cortical and subcortical memory regions.

Despite the discovery of gene variants linked to memory performance, understanding the genetic basis of adult human memory remains a challenge. Here, we devised an unsupervised framework that relies on spatial correlations between human transcriptome data and functional neuroimaging maps to uncover the genetic signatures of memory in functionally-defined cortical and subcortical memory regions. Results were validated with animal literature and showed that our framework is highly effective in identifying memory-related processes and genes compared to a control cognitive function. Genes preferentially expressed in cortical memory regions are linked to memory-related processes such as immune and epigenetic regulation. Genes expressed in subcortical memory regions are associated with neurogenesis and glial cell differentiation. Genes expressed in both cortical and subcortical memory areas are involved in the regulation of transcription, synaptic plasticity, and glutamate receptor signaling. Furthermore, distinct memory-associated genes such as PRKCD and CDK5 are linked to cortical and subcortical regions, respectively. Thus, cortical and subcortical memory regions exhibit distinct genetic signatures that potentially reflect functional differences in health and disease, and nominates gene candidates for future experimental investigations.

Progesterone induced Warburg effect in HEK293 cells is associated with post-translational modifications and proteasomal degradation of progesterone receptor membrane component 1

Progesterone (P4) is a major steroid hormone that has important effects on metabolism. The progesterone receptor membrane component 1 (PGRMC1) is a non-canonical P4 binding protein. The biological functions affected by PGRMC1 include cholesterol/steroid biosynthesis and metabolism, iron homeostasis and heme trafficking, autophagy, regulation of cell cycle and proliferation, cell migration and invasion. PGRMC1 has been an attractive target for therapeutic intervention in cancer and neurodegenerative disorders due to its biological role in promoting cell survival. P4 has been used in a number of clinical applications and is considered neuroprotective. The involvement of PGRMC1 in P4-mediated regulation of cellular glucose metabolism is not well studied. PGRMC1 is a 21 kDa protein but complex post-translational modifications (PTMs) lead to the existence of several high molecular mass proteins whose molecular function, intracellular distribution, and physiological relevancies are not fully known. Therefore, in this study, P4-PGRMC1-mediated cellular glucose metabolism and PTMs of PGRMC1 were studied using wild-type and CRISPR/Cas9 mediated PGRMC1 knockout (KO) human embryonic kidney-derived (HEK293) cell lines. A 70 kDa (p70) and 100 kDa (p100) PGRMC1 proteins were identified that are predominantly associated with endoplasmic reticulum/mitochondria and nuclear fractions in the cells, respectively. Phosphorylation, acetylation, ubiquitination, and sumoylation of native PGRMC1 under serum starvation were identified which provided an explanation for the higher molecular masses. This study indicates that P4-PGRMC1 signaling caused a rapid increase in glycolysis in the presence of oxygen (aerobic glycolysis) and a corresponding decrease in cellular respiration, known as the Warburg effect. Further, it was demonstrated that the P4-induced increase in glycolysis is associated with rapid proteasomal degradation of the p70 and reduction of the nuclear p100 protein level. P4 treatment also caused significant alteration in the dynamics of PGRMC1 PTMs and its association with potential interacting proteins. Overall, this study provides a hitherto unknown aspect of P4-PGRMC1 mediated signaling that changes basic cellular metabolism in HEK293 cells.

A Serum Protein Biomarker Panel Improves Outcome Prediction in Human Traumatic Brain Injury

Brain-enriched protein biomarkers of tissue fate are being introduced clinically to aid in traumatic brain injury (TBI) management. The aim of this study was to determine how concentrations of six different protein biomarkers, measured in samples collected during the first weeks after TBI, relate to injury severity and outcome. We included neurocritical care TBI patients that were prospectively enrolled from 2007 to 2013, all having one to three blood samples drawn during the first 2 weeks. The biomarkers analyzed were S100 calcium-binding protein B (S100B), neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1), tau, and neurofilament-light (NF-L). Glasgow Outcome Score (GOS) was assessed at 12 months. In total, 172 patients were included. All serum markers were associated with injury severity as classified on computed tomography scans at admission. Almost all biomarkers outperformed other known outcome predictors with higher levels the first 5 days, correlating with unfavorable outcomes, and UCH-L1 (0.260, pseduo-R²) displaying the best discrimination in univariate analyses. After adjusting for acknowledged TBI outcome predictors, GFAP and NF-L added most independent information to predict favorable/unfavorable GOS, improving the model from 0.38 to 0.51 pseudo-R². A correlation matrix indicated substantial covariance, with the strongest correlation between UCH-L1, GFAP, and tau (r = 0.827-0.880). Additionally, the principal component analysis exhibited clustering of UCH-L1 and tau, as well as GFAP, S100B, and NSE, which was separate from NF-L. In summary, a panel of several different protein biomarkers, all associated with injury severity, with different cellular origin and temporal trajectories, improve outcome prediction models.

Proteomic Atlas of the Human Brain in Alzheimer's Disease

The brain represents one of the most divergent and critical organs in the human body. Yet, it can be afflicted by a variety of neurodegenerative diseases specifically linked to aging, about which we lack a full biomolecular understanding of onset and progression, such as Alzheimer's disease (AD). Here we provide a proteomic resource comprising nine anatomically distinct sections from three aged individuals, across a spectrum of disease progression, categorized by quantity of neurofibrillary tangles. Using state-of-the-art mass spectrometry, we identify a core brain proteome that exhibits only small variance in expression, accompanied by a group of proteins that are highly differentially expressed in individual sections and broader regions. AD affected tissue exhibited slightly elevated levels of tau protein with similar relative expression to factors associated with the AD pathology. Substantial differences were identified between previous proteomic studies of mature adult brains and our aged cohort. Our findings suggest considerable value in examining specifically the brain proteome of aged human populations from a multiregional perspective. This resource can serve as a guide, as well as a point of reference for how specific regions of the brain are affected by aging and neurodegeneration.

Astrocytes in Neuropathologies Affecting the Frontal Cortex

To an increasing extent, astrocytes are connected with various neuropathologies. Astrocytes comprise of a heterogeneous population of cells with region- and species-specific properties. The frontal cortex exhibits high levels of plasticity that is required for high cognitive functions and memory making this region especially susceptible to damage. Aberrations in the frontal cortex are involved with several cognitive disorders, including Alzheimer’s disease, Huntington’s disease and frontotemporal dementia. Human induced pluripotent stem cells (iPSCs) provide an alternative for disease modeling and offer possibilities for studies to investigate pathological mechanisms in a cell type-specific manner. Patient-specific iPSC-derived astrocytes have been shown to recapitulate several disease phenotypes. Addressing astrocyte heterogeneity may provide an improved understanding of the mechanisms underlying neurodegenerative diseases.

Insights into human intrinsically disordered proteins from their gene expression profile

Expression level provides important clues about gene function. Previously, various efforts have been undertaken to profile human genes according to their expression level. Intrinsically disordered proteins (IDPs) do not adopt any rigid conformation under physiological conditions, however, are considered as an important functional class in all domains of life. Based on a human tissue-averaged gene expression level, previous studies showed that IDPs are expressed at a lower level than ordered globular proteins. Here, we examined the gene expression pattern of human ordered and disordered proteins in 32 normal tissues. We noticed that in most of the tissues, ordered and disordered proteins are expressed at a similar level. Moreover, in a number of tissues IDPs were found to be expressed at a higher level than ordered proteins. Rigorous statistical analyses suggested that the lower tissue-averaged gene expression level of IDPs (reported earlier) may be the consequence of their biased gene expression in some specific tissues and higher protein length. When we considered the gene repertory of each tissue we noticed that a number of human tissues (brain, testes, etc.) selectively express a higher fraction of disordered proteins, which help them to maintain higher protein connectivity by forming disordered binding motifs and to sustain their functional specificities. Our results demonstrated that the disordered proteins are indispensable in these tissues for their functional advantages.

The Cerebrospinal Fluid Neurogranin/BACE1 Ratio is a Potential Correlate of Cognitive Decline in Alzheimer's Disease

Background: In diagnosing Alzheimer’s disease (AD), ratios of cerebrospinal fluid (CSF) biomarkers, such as CSF Aβ_1-42/tau, have an improved diagnostic performance compared to the single analytes, yet, still a limited value to predict cognitive decline. Since synaptic dysfunction/loss is closely linked to cognitive impairment, synaptic proteins are investigated as candidate CSF AD progression markers.

Objective: We studied CSF levels of the postsynaptic protein neurogranin and protein BACE1, predominantly localized presynaptically, and their relation to CSF total-tau, Aβ_1-42, Aβ_1-40, and Aβ_1-38. All six analytes were considered as single parameters as well as ratios.

Methods: Every ELISA involved was based on monoclonal antibodies, including the BACE1 and neurogranin immunoassay. The latter specifically targets neurogranin C-terminally truncated at P75, a more abundant species of the protein in CSF. We studied patients with MCI due to AD (n = 38) and 50 dementia due to AD patients, as well as age-matched cognitively healthy elderly (n = 20). A significant subset of the patients was followed up by clinical and neuropsychologically (MMSE) examinations for at least one year.

Results: The single analytes showed statistically significant differences between the clinical groups, but the ratios of analytes indeed had a higher diagnostic performance. Furthermore, only the ratio of CSF neurogranin trunc P75/BACE1 was significantly correlated with the yearly decline in MMSE scores in patients with MCI and dementia due to AD, pointing toward the prognostic value of the ratio.

Conclusion: This is the first study demonstrating that the CSF neurogranin trunc P75/BACE1 ratio, reflecting postsynaptic/presynaptic integrity, is related to cognitive decline.

Derivation of a Three Biomarker Panel to Improve Diagnosis in Patients with Mild Traumatic Brain Injury

Background

Nearly 5 million emergency department (ED) visits for head injury occur each year in the United States, of which <10% of patients show abnormal computed tomography (CT) findings. CT negative patients frequently suffer protracted somatic, behavioral, and neurocognitive dysfunction. Our goal was to evaluate biomarkers to identify mild TBI (mTBI) in patients with suspected head injury.

Methods

An observational ED study of head-injured and control patients was conducted at Johns Hopkins University (HeadSMART). Head CT was obtained (ACEP criteria) in patients with Glasgow Coma Scale scores of 13–15 and aged 18–80. Three candidate biomarker proteins, neurogranin (NRGN), neuron-specific enolase (NSE), and metallothionein 3 (MT3), were evaluated by immunoassay (samples <24 h from injury). American Congress of Rehabilitation Medicine (ACRM) criteria were used for diagnosis of mTBI patients for model building. Univariate analysis, logistic regression, and random forest (RF) algorithms were used for data analysis in R. Overall, 662 patients were studied. Statistical models were built using 328 healthy controls and 179 mTBI patients.

Results

Median time from injury was 5.9 h (IQR, 4.0; range 0.8–24 h). mTBI patients had elevated NSE, but decreased MT3 versus controls (p < 0.01 for each). NRGN was also elevated but within 2–6 h after injury. In the derivation set, the best model to distinguish mTBI from healthy controls used three markers, age, and sex as covariates (C-statistic = 0.91, sensitivity 98%, specificity 72%). Panel test accuracy was validated with the 155 remaining ACRM+ mTBI patients. Applying the RF model to the ACRM+ mTBI validation set resulted in 78% correctly classified as mTBI (119/153). CT positive and CT negative validation subsets were 91% and 75% correctly classified. In samples taken <2 h from injury, 100% (10/10) samples classified correctly, indicating that hyperacute testing is possible with these biomarker assays. The model accuracy varied from 72–100% overall, and had greater accuracy with increasing severity, as shown by comparing CT+ with CT− (91% versus 75%), and Injury Severity Score ≥16 versus <16 (88% versus 72%, respectively). Objective blood tests, detecting NRGN, NSE, and MT3, can be used to identify mTBI, irrespective of neuroimaging findings.

Advantages of Structure-Based Drug Design Approaches in Neurological Disorders

OBJECTIVE

The purpose of the review is to portray the theoretical concept on neurological disorders from research data.

BACKGROUND

The freak changes in chemical response of nerve impulse causes neurological disorders. The research evidence of the effort done in the older history suggests that the biological drug targets and their effective feature with responsive drugs could be valuable in promoting the future development of health statistics structure for improved treatment for curing the nervous disorders.

METHODS

In this review, we summarized the most iterative theoretical concept of structure based drug design approaches in various neurological disorders to unfathomable understanding of reported information for future drug design and development.

RESULTS

On the premise of reported information we analyzed the model of theoretical drug designing process for understanding the mechanism and pathology of the neurological diseases which covers the development of potentially effective inhibitors against the biological drug targets. Finally, it also suggests the management and implementation of the current treatment in improving the human health system behaviors.

CONCLUSION

With the survey of reported information we concluded the development strategies of diagnosis and treatment against neurological diseases which leads to supportive progress in the drug discovery.

Serial Sampling of Serum Protein Biomarkers for Monitoring Human Traumatic Brain Injury Dynamics: A Systematic Review

BACKGROUND

The proteins S100B, neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and neurofilament light (NF-L) have been serially sampled in serum of patients suffering from traumatic brain injury (TBI) in order to assess injury severity and tissue fate. We review the current literature of serum level dynamics of these proteins following TBI and used the term "effective half-life" (t1/2) in order to describe the "fall" rate in serum.

MATERIALS AND METHODS

Through searches on EMBASE, Medline, and Scopus, we looked for articles where these proteins had been serially sampled in serum in human TBI. We excluded animal studies, studies with only one presented sample and studies without neuroradiological examinations.

RESULTS

Following screening (10,389 papers), n = 122 papers were included. The proteins S100B (n = 66) and NSE (n = 27) were the two most frequent biomarkers that were serially sampled. For S100B in severe TBI, a majority of studies indicate a t1/2 of about 24 h, even if very early sampling in these patients reveals rapid decreases (1-2 h) though possibly of non-cerebral origin. In contrast, the t1/2 for NSE is comparably longer, ranging from 48 to 72 h in severe TBI cases. The protein GFAP (n = 18) appears to have t1/2 of about 24-48 h in severe TBI. The protein UCH-L1 (n = 9) presents a t1/2 around 7 h in mild TBI and about 10 h in severe. Frequent sampling of these proteins revealed different trajectories with persisting high serum levels, or secondary peaks, in patients with unfavorable outcome or in patients developing secondary detrimental events. Finally, NF-L (n = 2) only increased in the few studies available, suggesting a serum availability of >10 days. To date, automated assays are available for S100B and NSE making them faster and more practical to use.

CONCLUSION

Serial sampling of brain-specific proteins in serum reveals different temporal trajectories that should be acknowledged. Proteins with shorter serum availability, like S100B, may be superior to proteins such as NF-L in detection of secondary harmful events when monitoring patients with TBI.

Linking deregulation of non-coding RNA to the core pathophysiology of Alzheimer's disease: An integrative review

The human genome encodes a vast repertoire of protein non-coding RNAs (ncRNA), some specific to the brain. MicroRNAs, which interfere with the translation of target mRNAs, are of particular interest since their deregulation has been implicated in neurodegenerative disorders like Alzheimer's disease (AD). However, it remains challenging to link the complex body of observations on miRNAs and AD into a coherent framework. Using extensive graphical support, this article discusses how a diverse panoply of miRNAs convergently and divergently impact (and are impacted by) core pathophysiological processes underlying AD: neuroinflammation and oxidative stress; aberrant generation of β-amyloid-42 (Aβ42); anomalies in the production, cleavage and post-translational marking of Tau; impaired clearance of Aβ42 and Tau; perturbation of axonal organisation; disruption of synaptic plasticity; endoplasmic reticulum stress and the unfolded protein response; mitochondrial dysfunction; aberrant induction of cell cycle re-entry; and apoptotic loss of neurons. Intriguingly, some classes of miRNA provoke these cellular anomalies, whereas others act in a counter-regulatory, protective mode. Moreover, changes in levels of certain species of miRNA are a consequence of the above-mentioned anomalies. In addition to miRNAs, circular RNAs, piRNAs, long non-coding RNAs and other types of ncRNA are being increasingly implicated in AD. Overall, a complex mesh of deregulated and multi-tasking ncRNAs reciprocally interacts with core pathophysiological mechanisms underlying AD. Alterations in ncRNAs can be detected in CSF and the circulation as well as the brain and are showing promise as biomarkers, with the ultimate goal clinical exploitation as targets for novel modes of symptomatic and course-altering therapy.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches.

A review of the clinical utility of serum S100B protein levels in the assessment of traumatic brain injury

Background

In order to improve injury assessment of brain injuries, protein markers of pathophysiological processes and tissue fate have been introduced in the clinic. The most studied protein “biomarker” of cerebral damage in traumatic brain injury (TBI) is the protein S100B. The aim of this narrative review is to thoroughly analyze the properties and capabilities of this biomarker with focus on clinical utility in the assessment of patients suffering from TBI.

Results

S100B has successfully been implemented in the clinic regionally (1) to screen mild TBI patients evaluating the need to perform a head computerized tomography, (2) to predict outcome in moderate-to-severe TBI patients, (3) to detect secondary injury development in brain-injured patients and (4) to evaluate treatment efficacy. The potential opportunities and pitfalls of S100B in the different areas usually refer to its specificity and sensitivity to detect and assess intracranial injury.

Conclusion

Given some shortcomings that should be realized, S100B can be used as a versatile screening, monitoring and prediction tool in the management of TBI patients.

A review of the clinical utility of serum S100B protein levels in the assessment of traumatic brain injury

BACKGROUND

In order to improve injury assessment of brain injuries, protein markers of pathophysiological processes and tissue fate have been introduced in the clinic. The most studied protein "biomarker" of cerebral damage in traumatic brain injury (TBI) is the protein S100B. The aim of this narrative review is to thoroughly analyze the properties and capabilities of this biomarker with focus on clinical utility in the assessment of patients suffering from TBI.

RESULTS

S100B has successfully been implemented in the clinic regionally (1) to screen mild TBI patients evaluating the need to perform a head computerized tomography, (2) to predict outcome in moderate-to-severe TBI patients, (3) to detect secondary injury development in brain-injured patients and (4) to evaluate treatment efficacy. The potential opportunities and pitfalls of S100B in the different areas usually refer to its specificity and sensitivity to detect and assess intracranial injury.

CONCLUSION

Given some shortcomings that should be realized, S100B can be used as a versatile screening, monitoring and prediction tool in the management of TBI patients.

CSF profiling of the human brain enriched proteome reveals associations of neuromodulin and neurogranin to Alzheimer's disease

Purpose

This study is part of a larger effort aiming to expand the knowledge of brain‐enriched proteins in human cerebrospinal fluid (CSF) and to provide novel insight into the relation between such proteins and different neurodegenerative diseases.

Experimental design

Here 280 brain‐enriched proteins in CSF from patients with Alzheimer's disease (AD), Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are profiled. In total, 441 human samples of ventricular CSF collected post mortem and lumbar CSF collected ante mortem are analyzed using 376 antibodies in a suspension bead array setup, utilizing a direct labelling approach.

Results

Among several proteins displaying differentiated profiles between sample groups, we focus here on two synaptic proteins, neuromodulin (GAP43) and neurogranin (NRGN). They are both found at elevated levels in CSF from AD patients in two independent cohorts, providing disease‐associated profiles in addition to verifying and strengthening previously observed patterns. Increased levels are also observed for patients for whom the AD diagnosis was not established at the time of sampling.

Conclusions and clinical relevance

These findings indicate that analyzing the brain‐enriched proteins in CSF is of particular interest to increase the understanding of the CSF proteome and its relation to neurodegenerative disorders. In addition, this study lends support to the notion that measurements of these synaptic proteins could potentially be of great relevance in future diagnostic tests for AD.

Protein profiling in serum after traumatic brain injury in rats reveals potential injury markers

INTRODUCTION

The serum proteome following traumatic brain injury (TBI) could provide information for outcome prediction and injury monitoring. The aim with this affinity proteomic study was to identify serum proteins over time and between normoxic and hypoxic conditions in focal TBI.

MATERIAL AND METHODS

Sprague Dawley rats (n=73) received a 3mm deep controlled cortical impact ("severe injury"). Following injury, the rats inhaled either a normoxic (22% O₂) or hypoxic (11% O₂) air mixture for 30min before resuscitation. The rats were sacrificed at day 1, 3, 7, 14 and 28 after trauma. A total of 204 antibodies targeting 143 unique proteins of interest in TBI research, were selected. The sample proteome was analyzed in a suspension bead array set-up. Comparative statistics and factor analysis were used to detect differences as well as variance in the data.

RESULTS

We found that complement factor 9 (C9), complement factor B (CFB) and aldolase c (ALDOC) were detected at higher levels the first days after trauma. In contrast, hypoxia inducing factor (HIF)1α, amyloid precursor protein (APP) and WBSCR17 increased over the subsequent weeks. S100A9 levels were higher in hypoxic-compared to normoxic rats, together with a majority of the analyzed proteins, albeit few reached statistical significance. The principal component analysis revealed a variance in the data, highlighting clusters of proteins.

CONCLUSIONS

Protein profiling of serum following TBI using an antibody based microarray revealed temporal changes of several proteins over an extended period of up to four weeks. Further studies are warranted to confirm our findings.

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q-Exactive HF Mass Spectrometer

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092.

Neuroproteomic profiling of human body fluids

Analysis of protein expression and abundance provides a possibility to extend the current knowledge on disease-associated processes and pathways. The human brain is a complex organ and dysfunction or damage can give rise to a variety of neurological diseases. Although many proteins potentially reflecting disease progress are originating from brain, the scarce availability of human tissue material has lead to utilization of body fluids such as cerebrospinal fluid and blood in disease-related research. Within the most common neurological disorders, much effort has been spent on studying the role of a few hallmark proteins in disease pathogenesis but despite extensive investigation, the signatures they provide seem insufficient to fully understand and predict disease progress. In order to expand the view the field of neuroproteomics has lately emerged alongside developing technologies, such as affinity proteomics and mass spectrometry, for multiplexed and high-throughput protein profiling. Here, we provide an overview of how such technologies have been applied to study neurological disease and we also discuss some important considerations concerning discovery of disease-associated profiles.

Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification

Remarkable progress continues on the annotation of the proteins identified in the Human Proteome and on finding credible proteomic evidence for the expression of "missing proteins". Missing proteins are those with no previous protein-level evidence or insufficient evidence to make a confident identification upon reanalysis in PeptideAtlas and curation in neXtProt. Enhanced with several major new data sets published in 2014, the human proteome presented as neXtProt, version 2014-09-19, has 16,491 unique confident proteins (PE level 1), up from 13,664 at 2012-12 and 15,646 at 2013-09. That leaves 2948 missing proteins from genes classified having protein existence level PE 2, 3, or 4, as well as 616 dubious proteins at PE 5. Here, we document the progress of the HPP and discuss the importance of assessing the quality of evidence, confirming automated findings and considering alternative protein matches for spectra and peptides. We provide guidelines for proteomics investigators to apply in reporting newly identified proteins.