Scalable Hypothalamic Arcuate Neuron Differentiation from Human Pluripotent Stem Cells Suitable for Modeling Metabolic and Reproductive Disorders.

The hypothalamus, composed of several nuclei, is essential for maintaining our body's homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.

Methotrexate-based PROTACs as DHFR-specific chemical probes.

Methotrexate (MTX) is a tight-binding dihydrofolate reductase (DHFR) inhibitor, used as both an antineoplastic and immunosuppressant therapeutic. MTX, like folate undergoes folylpolyglutamate synthetase-mediated γ-glutamylation, which affects cellular retention and target specificity. Mechanisms of MTX resistance in cancers include a decrease in MTX poly-γ-glutamylation and an upregulation of DHFR. Here, we report a series of potent MTX-based proteolysis targeting chimeras (PROTACs) to investigate DHFR degradation pharmacology and one-carbon biochemistry. These on-target, cell-active PROTACs show proteasome- and E3 ligase-dependent activity, and selective degradation of DHFR in multiple cancer cell lines. By comparison, treatment with MTX increases cellular DHFR protein expression. Importantly, these PROTACs produced distinct, less-lethal phenotypes compared to MTX. The chemical probe set described here should complement conventional DHFR inhibitors and serve as useful tools for studying one-carbon biochemistry and dissecting complex polypharmacology of MTX and related drugs. Such compounds may also serve as leads for potential autoimmune and antineoplastic therapeutics.

Whole-genome methylation analysis of aging human tissues identifies age-related changes in developmental and neurological pathways.

Age-associated changes in the DNA methylation state can be used to assess the pace of aging. However, it is not understood what mechanisms drive these changes and whether these changes affect the development of aging phenotypes and the aging process in general. This study was aimed at gaining a more comprehensive understanding of aging-related methylation changes across the whole genome, and relating these changes to biological functions. It has been shown that skeletal muscle and blood monocytes undergo typical changes with aging. Using whole-genome bisulfite sequencing, we sought to characterize the genome-wide changes in methylation of DNA derived from both skeletal muscle and blood monocytes, and link these changes to specific genes and pathways through enrichment analysis. We found that methylation changes occur with aging at the locations enriched for developmental and neuronal pathways regulated in these two peripheral tissues. These results contribute to our understanding of changes in epigenome in human aging.

Understanding the Human Aging Proteome Using Epidemiological Models.

Human aging is a complex multifactorial process associated with a decline of physical and cognitive function and high susceptibility to chronic diseases, influenced by genetic, epigenetic, environmental, and demographic factors. This chapter will provide an overview on the use of epidemiological models with proteomics data as a method that can be used to identify factors that modulate the aging process in humans. This is demonstrated with proteomics data from human plasma and skeletal muscle, where the combination with epidemiological models identified a set of mitochondrial, spliceosome, and senescence proteins as well as the role of energetic pathways such as glycolysis, and electron transport pathways that regulate the aging process.

Proteomics and Epidemiological Models of Human Aging.

Human aging is associated with a decline of physical and cognitive function and high susceptibility to chronic diseases, which is influenced by genetics, epigenetics, environmental, and socio-economic status. In order to identify the factors that modulate the aging process, established measures of aging mechanisms are required, that are both robust and feasible in humans. It is also necessary to connect these measures to the phenotypes of aging and their functional consequences. In this review, we focus on how this has been addressed from an epidemiologic perspective using proteomics. The key aspects of epidemiological models of aging can be incorporated into proteomics and other omics which can provide critical detailed information on the molecular and biological processes that change with age, thus unveiling underlying mechanisms that drive multiple chronic conditions and frailty, and ideally facilitating the identification of new effective approaches for prevention and treatment.

Minireview: Novel Micropeptide Discovery by Proteomics and Deep Sequencing Methods.

A novel class of small proteins, called micropeptides, has recently been discovered in the genome. These proteins, which have been found to play important roles in many physiological and cellular systems, are shorter than 100 amino acids and were overlooked during previous genome annotations. Discovery and characterization of more micropeptides has been ongoing, often using -omics methods such as proteomics, RNA sequencing, and ribosome profiling. In this review, we survey the recent advances in the micropeptides field and describe the methodological and conceptual challenges facing future micropeptide endeavors.

Ribosome profiling analysis of human skeletal muscle identifies reduced translation of mitochondrial proteins with age.

With advancing age, human muscle loses strength and function, but the molecular causes of these losses are unknown. Skeletal muscle shows an age-dependent decline in the levels of different proteins, but whether such decline is associated with reduced translation has not been studied. To address this gap of knowledge, we used the technique of ribosome profiling to study translation in muscle from middle-aged and old individuals. Using ribosome occupancy as a measure of translation status, several mRNAs showed differential translation with age. Older age was associated with lower translation of myosin and titin isoforms and more broadly with the translation of proteins involved in oxidative phosphorylation encoded by the mitochondrial genome. Based on our findings, we propose that mitochondrial proteins are less translated in old skeletal muscle.

Translational Control during Cellular Senescence.

Senescence is a state of long-term cell cycle arrest that arises in cells that have incurred sublethal damage. While senescent cells no longer replicate, they remain metabolically active and further develop unique and stable phenotypes that are not present in proliferating cells. On one hand, senescent cells increase in size, maintain an active mTORC1 complex, and produce and secrete a substantial amount of inflammatory proteins as part of the senescence-associated secretory phenotype (SASP). On the other hand, these progrowth phenotypes contrast with the p53-mediated growth arrest typical of senescent cells that is associated with nucleolar stress and an inhibition of rRNA processing and ribosome biogenesis. In sum, translation in senescent cells paradoxically comprises both a global repression of translation triggered by DNA damage and a select increase in the translation of specific proteins, including SASP factors.

Blood DNA Methylation and Aging: A Cross-Sectional Analysis and Longitudinal Validation in the InCHIANTI Study.

Changes in DNA methylation have been found to be highly correlated with aging in humans, but causes or consequences of these changes are not understood. We characterized the DNA methylomes of several hundred people in the Invecchiare in Chianti study to identify DNA sites in which percent methylation was systematically different with age. Then, we tested the hypothesis that changes of percent methylation in the same DNA sites occur longitudinally for the same DNA sites in the same subjects. We identified six differentially methylated regions in which percent methylation showed robust longitudinal changes in the same direction. We then describe functions of the genes near these differentially methylated regions and their potential relationship with aging, noting that the genes appear to regulate metabolism or cell type specificity. The nature of transcription factor binding sites in the vicinity of these differentially methylated regions suggest that these age-associated methylation changes reflect modulation of two biological mechanisms: the polycomb repressive complex 2, a protein complex that trimethylates histone H3 on lysine 27, and the transcriptional repressor CCCTC-binding factor or CTCF, both of which are regulators of chromatin architecture. These findings are consistent with the idea that changes in methylation with aging are of adaptive nature.

A methodology for discovering novel brain-relevant peptides: Combination of ribosome profiling and peptidomics.

Brain derived peptides function as signaling molecules in the brain and regulate various physiological and behavioral processes. The low abundance and atypical fragmentation of these brain derived peptides makes detection using traditional proteomic methods challenging. In this study, we introduce and validate a new methodology for the discovery of novel peptides derived from mammalian brain. This methodology combines ribosome profiling and mass spectrometry-based peptidomics. Using this framework, we have identified a novel peptide in mouse whole brain whose expression is highest in the basal ganglia, hypothalamus and amygdala. Although its functional role is unknown, it has been previously detected in peripheral tissue as a component of the mRNA decapping complex. Continued discovery and studies of novel regulating peptides in mammalian brain may also provide insight into brain disorders.

Discovery proteomics in aging human skeletal muscle finds change in spliceosome, immunity, proteostasis and mitochondria.

A decline of skeletal muscle strength with aging is a primary cause of mobility loss and frailty in older persons, but the molecular mechanisms of such decline are not understood. Here, we performed quantitative proteomic analysis from skeletal muscle collected from 58 healthy persons aged 20 to 87 years. In muscle from older persons, ribosomal proteins and proteins related to energetic metabolism, including those related to the TCA cycle, mitochondria respiration, and glycolysis, were underrepresented, while proteins implicated in innate and adaptive immunity, proteostasis, and alternative splicing were overrepresented. Consistent with reports in animal models, older human muscle was characterized by deranged energetic metabolism, a pro-inflammatory environment and increased proteolysis. Changes in alternative splicing with aging were confirmed by RNA-seq analysis. We propose that changes in the splicing machinery enables muscle cells to respond to a rise in damage with aging.

Modifications in acute phase and complement systems predict shifts in cognitive status of HIV-infected patients.

BACKGROUND: The prevalence of HIV-associated neurocognitive disorders (HAND) has not changed considerably in the last two decades. Potent antiretroviral therapy has shifted the severity of HAND to milder phenotypes, but excess morbidity and mortality continue to be associated with HAND. Changes in numerous markers of immune function, inflammation, and cellular stress have been repeatedly associated with HAND, but the underlying systems that drive these changes have not been identified. METHOD: In this study, we used systems informatics to interrogate the cerebrospinal fluid proteomic content of longitudinal samples obtained from HIV-infected adults with stably unimpaired, stably impaired, worsening, or improving neurocognitive performance. RESULTS AND CONCLUSION: The patterns of change in cerebrospinal fluid protein content implicated the induction of acute phase and complement systems as important regulators of neurocognitive status. Worsening neurocognitive performance was preceded by induction of acute phase and complement systems, whereas improving neurocognitive performance was preceded by a downregulation of these systems.

Integrated microfluidic chip and online SCX separation allows untargeted nanoscale metabolomic and peptidomic profiling.

Metabolomics and peptidomics are systems biology approaches in which broad populations of molecular species produced in a cell or tissue sample are identified and quantified. These two molecular populations, metabolites and peptides, can be extracted from tissues in a similar fashion, and we therefore have here developed an integrated platform for their extraction and characterization. This was accomplished by liquid-liquid extraction of peptides and metabolites from tissue samples and online strong cation exchange (SCX) separation to allow characterization of each population individually. The platform was validated both by a mixed set of purified standards and by an analysis of splenic tissue from SIV-infected macaques, showing both good reproducibility in chromatography, with relative standard deviation (RSD) of hold time less than 0.4%, and clear separation of charge state, with ∼ 95% of molecular features in SCX separated runs at charge states of +1 or +2. Finally, we used this platform to analyze the physiological response to infection in the spleen, showing that the spleen contains an abundance of hemoglobin-derived peptides, which do not appear to change in response to infection, and that there appears to be a large and variable metabolic response to infection. We therefore present a method for peptidomic and metabolomic profiling which is simple, robust, and easy to implement.

Bioinformatics tools and challenges in structural analysis of lipidomics MS/MS data.

Lipidomics, the systematic study of the lipid composition of a cell or tissue, is an invaluable complement to knowledge gained by genomics and proteomics research. Mass spectrometry provides a means to detect hundreds of lipids in parallel, and this includes low abundance species of lipids. Nevertheless, frequently occurring isobaric and isomeric lipid species complicate lipidomics analyses from an analytical and bioinformatics perspective. Various MS/MS strategies have evolved to resolve ambiguous identifications of lipid species, and these strategies have been supported by corresponding bioinformatics analysis tools. This review intends to familiarize readers with available bioinformatics MS/MS analysis tools and databases, the structural information obtainable from these, and their applicability to different MS/MS strategies. Finally, future challenges in detecting double bond positions are investigated from a bioinformatics perspective.

Data maximization by multipass analysis of protein mass spectra.

With the proliferation of search engines for the analysis of MS data, multisearch techniques aimed at boosting the discriminating power of the search engines' score functions have recently become popular. Much statistical and algorithmic work has been done, therefore, in order to be able to combine and parse multiple search streams. However, multisearch techniques suffer from long run times, and may have little impact on false negatives because of similar peptide filtering heuristics between searches. This review focuses, rather, on multipass techniques, which use the results of one search to guide the selection of spectra, parameters and sequences in subsequent searches. This reduces the number of false-negative peptide identifications due to peptide candidate filtering while preserving statistical significance of existing (correct) identifications. Furthermore, this technique avoids substantial increases in running time and, by limiting the search space, does not reduce the statistical significance of correct identifications or introduce a statistically significant number of false-positive identifications. However, we argue that the existing combiner tools are not reliably applicable to these multipass situations, because of algorithmic assumptions about search space and statistical assumptions about the rate of true positives. Here we provide an overview of the advantages of and issues in multipass analysis techniques, the existing methods and workflows available to proteomic researchers, and the unsolved statistical and algorithmic issues amenable to future research.

OMSSAGUI: An open-source user interface component to configure and run the OMSSA search engine.

We here present a user-friendly and extremely lightweight tool that can serve as a stand-alone front-end for the Open MS Search Algorithm (OMSSA) search engine, or that can directly be used as part of an informatics processing pipeline for MS driven proteomics. The OMSSA graphical user interface (OMSSAGUI) tool is written in Java, and is supported on Windows, Linux, and OSX platforms. It is an open source under the Apache 2 license and can be downloaded from http://code.google.com/p/mass-spec-gui/.