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Uhlen, M.

Publications and source records attributed to Uhlen, M..

At least 37 records · Page 2Linked to original sources
bioRxiv2022

Expression of substance P, NPY and their Receptors Is Altered in Major Depression

BACKGROUNDMajor depressive disorder (MDD) is a serious disease and a burden to patients, families and society. Rodent experiments and human studies suggest that several neuropeptide systems, including substance P(SP)/tachykinin, neuropeptide Y(NPY) and their G protein-coupled receptors are involved in mood regulation. METHODSWe assessed the transcript levels (qPCR) of SP/tachykinin and NPY systems in five regions from postmortem brains of male and female depressed subjects who committed suicide (DSS) and controls: dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), the dorsal raphe nucleus (DRN), locus coeruleus (LC) and medullary raphe nuclei (MRN). We also analysed human LC neurons isolated using LCM with Smart-seq2 RNA sequencing. RESULTSTranscripts for all nine members were detected in male and female controls with marked regional variations of the raw CT values and with the highest levels for several tachykinin and tachykinin receptor transcripts in the DRN and for NPY and NPYR transcripts in the PFC regions. Significant sex differences for controls were recorded only in the DRN (NPYR2 >in females) and LC (TAC3 and NPY >in females). Elevated expression in DSS was recorded in (i) DLPFC for SP, TAC and TAC3 in females, SP in males, and NPYR1 in both sexes; and (ii) LC for all tachykinin family transcripts in females, SP, TACR1 and TACR3 in males, NPY in both sexes, and NPYR1 in males. CONCLUSIONSThe selective perturbation of neuropeptide systems in MDD patients may assist in the search for novel treatment strategies for subjects afflicted by this grave disorder.

neuroscience↗
bioRxiv2022

Deciphering the determinants of recombinant protein yield across the human secretome

Mammalian cells are critical hosts for the production of most therapeutic proteins and many proteins for biomedical research. While cell line engineering and bioprocess optimization have yielded high protein titers of some recombinant proteins, many proteins remain difficult to express. Here, we decipher the factors influencing yields in Chinese hamster ovary (CHO) cells as they produce 2165 different proteins from the human secretome. We demonstrate that variation within our panel of proteins cannot be explained by transgene mRNA abundance. Analyzing the expression of the 2165 human proteins with machine learning, we find that protein features account for only 15% of the variability in recombinant protein yield. Meanwhile, transcriptomic signatures account for 75% of the variability across 95 representative samples. In particular, we observe divergent signatures regarding ER stress and metabolism among the panel of cultures expressing different recombinant proteins. Thus, our study unravels the factors underlying the variation on recombinant protein production in CHO and highlights transcriptomics signatures that could guide the rational design of CHO cell systems tailored to specific proteins.

systems biology↗
bioRxiv2022

Multiplexed selectivity screening of anti-GPCR antibodies

G protein-coupled receptors (GPCRs) control critical cellular signaling pathways. Therapeutic agents, such as antibodies (Abs), are being developed to modulate GPCR signaling pathways. However, validating the selectivity of anti-GPCR Abs is challenging due to sequence similarities of individual receptors within GPCR subfamilies. To address this, we developed a multiplexed immunoassay to test >400 anti-GPCR Abs from the Human Protein Atlas targeting a customized library of 215 expressed and solubilized GPCRs representing all GPCR subfamilies. We found that ~61% of Abs were selective for their intended target, ~11% to bind off-target, and ~28% not to bind any GPCR. Antigens of on-target Abs were, on average, significantly longer, more disordered, and less likely to be buried in the interior of the GPCR protein than the other Abs. These results provide important insights into the immunogenicity of GPCR epitopes and form a basis for the design of therapeutic Abs and the detection of pathological auto-antibodies. TEASERA multiplexed library-to-library selectivity analysis of 400 anti-GPCR antibodies within subfamilies of 200 solubilized receptors.

biochemistry↗
bioRxiv2022

Genome-wide single cell annotation of the human protein-coding genes

An important quest for the life science community is to deliver a complete annotation of the human building-blocks of life, the genes and the proteins. Here, we report on a genome-wide effort to annotate all protein-coding genes based on single cell transcriptomics data representing all major tissues and organs in the human body, integrated with data from bulk transcriptomics and antibody-based tissue profiling. Altogether, 25 tissues have been analyzed with single cell transcriptomics resulting in genome-wide expression in 444 single cell types using a strategy involving pooling data from individual cells to obtain genome-wide expression profiles of individual cell type. We introduce a new genome-wide classification tool based on clustering of similar expression profiles across single cell types, which can be visualized using dimensional reduction maps (UMAP). The clustering classification is integrated with a new "tau" score classification for all protein-coding genes, resulting in a measure of single cell specificity across all cell types for all individual genes. The analysis has allowed us to annotate all human protein-coding genes with regards to function and spatial distribution across individual cell types across all major tissues and organs in the human body. A new version of the open access Human Protein Atlas (www.proteinatlas.org) has been launched to enable researchers to explore the new genome-wide annotation on an individual gene level.

systems biology↗
bioRxiv2022

Metabolic modelling of the human gut microbiome in type 2 diabetes patients in response to metformin treatment

The human gut microbiome has been associated with several metabolic disorders including type 2 diabetes. Understanding metabolic changes in the gut microbiome is important to elucidate the role of gut bacteria in regulating host metabolism. Here, we used available metagenomics data from a metformin study, together with genome-scale metabolic modelling of the key bacteria in individual and community-level to investigate the mechanistic role of the gut microbiome in response to metformin. Individual modelling predicted that species that are increased after metformin treatment have higher growth rates in comparison to species that are decreased after metformin treatment. Gut microbial enrichment analysis showed prior to metformin treatment pathways related to the hypoglycemic effect were enriched. Our observations highlight how the key bacterial species after metformin treatment have commensal and competing behavior, and how their cellular metabolism changes due to different nutritional environment. Integrating different diets showed there were specific microbial alterations between different diets. These results show the importance of the nutritional environment and how the dietary guidelines may improve drug efficiency through the gut microbiota.

systems biology↗
bioRxiv2022

Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning

Background & AimsNon-alcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver pathologies. However, not medical treatment has been approved for the treatment of the disease. In our previous study, we found PKLR could be a potential target for treatment of NALFD. Here, the aim is to investigate the effect of PKLR in in vivo model and perform drug repositioning to identify a drug candidate for treatment of NAFLD. MethodsBiopsies from liver, muscle, white adipose tissue and heart were obtained from control and PKLR knockout mice fed with chow and high sucrose diets. Lipidomics as well as transcriptmics analyses were conducted using these tissue samples. In addition, a computational drug repositioning analysis was performed and drug candidates were identified. The drug candidates were finally tested in both in vitro and in vivo models to evaluated their toxicity and efficacy. ResultsThe Pklr KO reversed the increased hepatic triglyceride level in mice fed with high sucrose diet and partly recovered the transcriptomic changes in liver as well as other three tissues. Both liver and white adipose tissues exhibited dysregulated circadian transcriptomic profiles, and these dysregulations were reversed by hepatic knockout of Pklr. In addition, 10 small molecule drugs were identified as potential inhibitor of PKLR by the drug repositioning pipeline, and two of them significantly inhibited both the PKLR expression and triglyceride level in in vitro model. Finally, the two selected small molecule drugs were evaluated in in vivo rat models and it was demonstrated that these drugs attenuated hepatic steatosis without side effect on other tissues. ConclusionIn conclusion, our study provided biological insights about the critical role of PKLR in NAFLD progression and proposed a treatment strategy for NAFLD patients, which has been validated in preclinical experiment.

systems biology↗
bioRxiv2021

GutMicroNet: an interactive platform for gut microbiome interaction exploration

The human gut microbiome data has been proven to be a powerful tool to understand the human body in both health and disease conditions. However, understanding their complex interactions and impact on the human body remains a challenging task. Unravelling the species-level interactions could allow us to study the causality of the microbiome. Moreover, it could lead us to better understand the underlying mechanisms of complex diseases and, subsequently, the discovery of new therapeutic targets. Given these challenges and benefits, it has become evident that a freely accessible and centralized platform for presenting gut microbiome interaction is essential to untangle the complexity and open multiple new paths and opportunities in disease- and drug-related research. Here, we present GutMicroNet, an interactive visualization platform of human gut microbiome interaction networks. We generated 45 gut microbiome co-abundance networks from various geographical origins, gender, and diseases based on the data presented in the Human Gut Microbiome Atlas. This interactive platform includes more than 1900 gut microbiome species and allows users to query multiple species at the same time based on their interests and adjust it based on the statistical properties. Moreover, users can download publication-ready figures or network information for further analysis. The platform can be accessed freely on https://gutmicro.net without any login requirements or limitations, including access to the full networks data.

systems biology↗
bioRxiv2021

A network-based approach reveals the dysregulated transcriptional regulation in non-alcohol fatty liver disease

Non-alcohol-related fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogenous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1 and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitated our understanding of the regulatory mechanism of these perturbed TFs and associated biological processes.

systems biology↗
bioRxiv2021

Systems analysis reveals ageing-related perturbations in retinoids and sex hormones in Alzheimer's and Parkinson's diseases

Neurodegenerative diseases (NDDs), including Alzheimers (AD) and Parkinsons diseases (PD), are complex heterogeneous diseases with highly variable patient responses to treatment. Due to the growing evidence for ageing-related clinical and pathological commonalities between AD and PD, these diseases have recently been studied in tandem. In this study, we analyse transcriptomic data from AD and PD patients, and stratify these patients into three subclasses with distinct gene expression and metabolic profiles. Through integrating transcriptomic data with a genome-scale metabolic model and validating our findings by network exploration and co-analysis using a zebrafish ageing model, we identify retinoids as a key ageing-related feature in all subclasses of AD and PD. We also demonstrate that the dysregulation of androgen metabolism by three different independent mechanisms is a source of heterogeneity in AD and PD. Taken together, our work highlights the need for stratification of AD/PD patients and development of personalised and precision medicine approaches based on the detailed characterisation of these subclasses.

systems biology↗
bioRxiv2021

Integrative functional analysis uncovers metabolic differences between Candida species

Candida species are a dominant constituent of the human mycobiome and a better understanding of their metabolism from a fungal perspective can provide key insights into their ability to cause pathogenesis. Here, we have developed the BioFung database - a fungal specific tool for functional annotation using the KEGG database that provides an efficient method for annotation of protein-encoding gene. Analysis of carbohydrate-active enzyme (CAZymes) and BioFung, uncovered core and accessory features across Candida species demonstrating plasticity, adaptation to the environment and acquired features. Integerative functional analysis revealed that all Candida species can employ amino acid metabolism. However, metabolomics revealed that only a specific cluster of species (AGAu species - C. albicans, C. glabrata and C. auris) utilised amino acid metabolism. We identified critical metabolic pathways in the AGAu clusters with biomarkers and anti-fungal target potential in the CAZyme profile, polyamine, choline and fatty acid biosynthesis pathways. This study, combining genomic analysis, metabolomics and gene expression validation, highlights the metabolic diversity within AGAu species that underlies their remarkable ability to dominate the mycobiome and cause disease.

systems biology↗
bioRxiv2021

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

BackgroundRisk prediction is crucial for early detection and prognosis of breast cancer. Circulating plasma proteins could provide a valuable source to increase the validity of risk prediction models, however, no such markers have yet been identified for clinical use. MethodsEDTA plasma samples from 183 breast cancer cases and 366 age-matched controls were collected prior to diagnosis from the Swedish breast cancer cohort KARMA. The samples were profiled on 700 circulating proteins using an exploratory affinity proteomics approach. Linear association analyses were performed on case-control status and a data-driven analysis strategy was applied to cluster the women on their plasma proteome profiles in an unsupervised manner. The resulting clusters were subsequently annotated for the differences in phenotypic characteristics, clinical parameters, and genetic risk. ResultsUsing the data-driven approach we identified five clusters with distinct proteomic plasma profiles. Women in a particular sub-group (cluster 1) were significantly more likely to have used menopausal hormonal therapy (MHT), more likely to get a breast cancer diagnosis, and were older compared to the remaining clusters. The levels of circulating proteins in cluster 1 were decreased for proteins related to DNA repair and cell replication and increased for proteins related to mammographic density and female tissues. In contrast, classical dichotomous case-control analyses did not reveal any proteins significantly associated with future breast cancer. ConclusionUsing a data-driven approach, we identified a subset of women with circulating proteins associated with previous use of MHT and risk of breast cancer. Our findings point to the potential long-lasting effects of MHT on the circulating proteome even after ending the treatment, and hence provide valuable insights concerning risk predication of breast cancer. HighlightsO_LICurrent risk prediction models use a variety of factors to identify women at risk of developing breast cancer. C_LIO_LIProteins circulating in blood represent an attractive but currently still underrepresented source of candidates serving as molecular risk factors. C_LIO_LIPlasma proteomes from women participating in a prospective breast cancer cohort study were studied for proteomic risk factors related to a future breast cancer diagnosis. C_LIO_LIUsing data-driven approaches, women with future breast cancers and previous use of menopausal hormone therapy were identified based on their circulating proteins. C_LIO_LIMenopausal hormone therapy was found to altered the levels of the circulating proteins even years after the treatment ended. C_LI

systems biology↗
bioRxiv2021

Combined Metabolic Activators decrease liver steatosis by activating mitochondrial metabolism in a Golden Syrian hamster study

The prevalence of non-alcohol fatty liver disease (NAFLD), defined as the livers excessive fat accumulation, continues to increase dramatically. We have recently revealed the molecular mechanism underlying NAFLD using in-depth multi-omics profiling and identified that combined metabolic activators (CMA) could be administered to decrease the amount of hepatic steatosis (HS) in mouse model and NAFLD patients based on systems analysis. Here, we investigated the effects of a CMA including L-carnitine, N-acetyl-l-cysteine, nicotinamide riboside and betaine on a Golden Syrian hamster NAFLD model fed with HFD, and found that HS was decreased with the administration of CMA. To explore the mechanisms involved in the clearance HS, we generated liver transcriptomics data before and after CMA administration, and integrated these data using liver-specific genome-scale metabolic model of liver tissue. We systemically determined the molecular changes after the supplementation of CMAs and found that it activates mitochondria in the liver tissue by modulating the global fatty acid, amino acids, antioxidant and folate metabolism.

systems biology↗
bioRxiv2021

The Reactobiome Unravels a New Paradigm in Human Gut Microbiome Metabolism

Changes in microbial metabolism have been used as the main approach to assess function and elucidate environmental and host-microbiome interactions. This can be hampered by uncharacterised metagenome species and lack of metabolic annotation. To address this, we present a comprehensive computational platform for population stratification based on microbiome composition, the underlying metabolic potential and generation of metagenome species and community level metabolic models. We revisit the concepts of enterotype and microbiome richness introducing the reactobiome as a stratification method to unravel the metabolic features of the human gut microbiome. The reactobiome encapsulates resilience and microbiome dysbiosis at a functional level. We describe five reactotypes in healthy populations from 16 countries, with specific amino acid, carbohydrate and xenobiotic metabolic features. The validity of the approach was tested to unravel host-microbiome and environmental interactions by applying the reactobiome analysis on a one-year Swedish longitudinal cohort, integrating gut metagenomics, plasma metabolomics and clinical data.

systems biology↗
bioRxiv2021

Large field of view-spatially resolved transcriptomics at nanoscale resolution

Spatially resolved transcriptomic technologies are promising tools to study cell fate decisions in a physical microenvironment, which is fundamental for enhancing our knowledge of mammalian development. However, the imbalance between resolution, transcript capture and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation mammalian embryos. Here, we combined DNA nanoball (DNB) patterned arrays and tissue RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution and sensitivity. We have applied Stereo-seq to study the kinetics and directionality of transcriptional variation in a time course of mouse organogenesis. We used this information to gain insight into the molecular basis of regional specification, neuronal migration and differentiation in the developing brain. Furthermore, we mapped the expression of a panel of developmental disease-related loci on our global transcriptomic maps to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes an essential resource to investigate longstanding questions concerning normal and abnormal mammalian development.

cell biology↗
bioRxiv2020

Revealing tissue-specific metabolic crosstalk after a myocardial infarction

Abstract/SummaryMyocardial infarction (MI) promotes a range of systemic effects, many of which are unknown. Here, we investigated the alterations associated with MI progression in heart and other metabolically active tissues (liver, skeletal muscle, and adipose) in a mouse model of MI (induced by ligating the left ascending coronary artery) and sham-operated mice. We performed a genome-wide transcriptomic analysis on tissue samples obtained 6- and 24-hours post MI or sham operation. By generating tissue-specific biological networks, we observed: (1) dysregulation in multiple biological processes (including immune system, mitochondrial dysfunction, fatty-acid beta-oxidation, and RNA and protein processing) across multiple tissues post MI; and (2) tissue-specific dysregulation in biological processes in liver and heart post MI. Finally, we validated our findings in two independent MI cohorts. Overall, our integrative analysis highlighted both common and specific biological responses to MI across a range of metabolically active tissues.

systems biology↗
bioRxiv2020

The protein expression profile of ACE2 in human tissues

The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is Angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across >150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitutes an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.

cell biology↗
bioRxiv2020

Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling

BackgroundPrecision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate. MethodsTo provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals short-term health trajectories. FindingsWe found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed both stable and fluctuating proteins in the circulation, as well as networks of proteins that covaried over time. For each participant, there were unique protein profiles and some of these could be explained by associations to genetic variants. InterpretationThis study demonstrates that there was noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. Longitudinal profiling of circulating proteomes has the potential to enable a more personal hence precise assessment of health states, and thereby provide a valuable component of precision medicine approaches. FundingThis work was supported by the Erling Persson Foundation for the KTH Centre for Precision Medicine and the Swedish Heart and Lung Foundation for the SCAPIS project. We also acknowledge the Knut and Alice Wallenberg Foundation for funding the Human Protein Atlas project, Science for Life Laboratory for Plasma Profiling Facility, and the Swedish Research Council (Grant no 2017-00641).

biochemistry↗
bioRxiv2020

Evolution from adherent to suspension - systems biology of HEK293 cell line development

The need for new safe and efficacious therapies has led to an increased focus on biologics produced in mammalian cells. The human cell line HEK293 has bio-synthetic potential for human-like production and is today used for manufacturing of several therapeutic proteins and viral vectors. Despite this increasing popularity there is still limited knowledge of the detailed genetic and composition of derivatives of this strain. Here we present a genomic, transcriptomic and metabolic gene analysis of six of the most widely used HEK293 cell lines. Changes in gene copy and expression between industrial progeny cell lines and the original HEK293 were associated with cellular component organization, cell motility and cell adhesion. Changes in gene expression between adherent and suspension derivatives highlighted switching in cholesterol biosynthesis and expression of five key genes (RARG, ID1, ZIC1, LOX and DHRS3), a pattern validated in 63 human adherent or suspension cell lines of other origin.

systems biology↗