Publications by authors named "Manuel Garcia-Albornoz"

Somatic mutations commonly occur in hematopoietic stem cells (HSCs). Some mutant clones outgrow through clonal hematopoiesis (CH) and produce mutated immune progenies shaping host immunity. Individuals with CH are asymptomatic but have an increased risk of developing leukemia, cardiovascular and pulmonary inflammatory diseases, and severe infections.

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  • Researchers identified a new population of human CD34 hematopoietic stem cells (HSCs) called EPCR HSCs, which exhibit exceptional self-renewal and repopulating abilities, with a frequency of about 1 in 3 cells being stem cells.
  • The EPCR HSCs display a unique gene expression profile that allows them to produce multiple blood cell lineages both in living organisms and lab settings.
  • This discovery provides a clearer picture of the hierarchy and organization of human hematopoietic stem cells, making it easier to study stem cell behavior in post-natal tissues.
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  • Unicellular organisms adjust their metabolism to manage growth and maintenance when environmental conditions change, involving a re-allocation of resources under specific cellular limitations.
  • A detailed metabolic model of yeast was developed, incorporating reactions related to protein synthesis and degradation, which helps predict metabolic activity and protein expression based on growth optimization.
  • The model reveals that under limited glucose, mitochondrial restrictions affect growth (e.g., the Crabtree effect), while excess sugars lead to constraints on cytosolic volume, influencing metabolic strategies and protein profiles.
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The bone-marrow (BM) niche is the spatial environment composed by a network of multiple stromal components regulating adult hematopoiesis. We use multi-omics and computational tools to analyze multiple BM environmental compartments and decipher their mutual interactions in the context of acute myeloid leukemia (AML) xenografts. Under homeostatic conditions, we find a considerable overlap between niche populations identified using current markers.

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  • Intensive care COVID-19 patients experience a significant drop in hemoglobin levels but an increase in nucleated red blood cells, indicating the virus may trigger stress-related blood cell production.
  • The study identifies that ACE2, which peaks during blood cell production, makes early erythroid progenitors (specific stem cells that develop into red blood cells) particularly susceptible to SARS-CoV-2 infection.
  • Findings reveal that SARS-CoV-2 can infect these progenitor cells, contributing to understanding severe COVID-19 symptoms and the virus's potential to spread and cause local inflammation in various tissues, including the bone marrow.
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Acute myeloid leukemia (AML) disrupts the generation of normal blood cells, predisposing patients to hemorrhage, anemia, and infections. Differentiation and proliferation of residual normal hematopoietic stem and progenitor cells (HSPCs) are impeded in AML-infiltrated bone marrow (BM). The underlying mechanisms and interactions of residual hematopoietic stem cells (HSCs) within the leukemic niche are poorly understood, especially in the human context.

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Protein biosynthesis is energetically costly, is tightly regulated and is coupled to stress conditions including glucose deprivation. RNA polymerase III (RNAP III)-driven transcription of tDNA genes for production of tRNAs is a key element in efficient protein biosynthesis. Here we present an analysis of the effects of altered RNAP III activity on the proteome and metabolism under glucose-rich conditions.

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Temperature fluctuation is a common environmental stress that elicits a molecular response in order to maintain intracellular protein levels. Here, for the first time, we report a comprehensive temporal and quantitative study of the proteome during a 240 minute heat stress, using label-free mass spectrometry. We report temporal expression changes of the hallmark heat stress proteins, including many molecular chaperones, tightly coupled to their protein clients.

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Background: Understanding the underlying molecular mechanisms in human diseases is important for diagnosis and treatment of complex conditions and has traditionally been done by establishing associations between disorder-genes and their associated diseases. This kind of network analysis usually includes only the interaction of molecular components and shared genes. The present study offers a network and association analysis under a bioinformatics frame involving the integration of HUGO Gene Nomenclature Committee approved gene symbols, KEGG metabolic pathways and ICD-10-CM codes for the analysis of human diseases based on the level of inclusion and hypergeometric enrichment between genes and metabolic pathways shared by the different human disorders.

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Analysis of large data sets using computational and mathematical tools have become a central part of biological sciences. Large amounts of data are being generated each year from different biological research fields leading to a constant development of software and algorithms aimed to deal with the increasing creation of information. The BioMet Toolbox 2.

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