Refine
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
- HAI‐1 (1)
- HGF (1)
- LUCA (1)
- hypoxia (1)
- metabolic pathway (1)
- ortholog search (1)
- phylogenetic profile (1)
- proliferation (1)
- sequence evolution (1)
- tumor‐associated macrophages (1)
Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. However, the similarity between orthologs decays with time, and ultimately it becomes insufficient to infer common ancestry. This leaves ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the "evolutionary traceability" as a measure that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. Using yeast, we show that genes that were thought to date back to the last universal common ancestor are of high traceability. Their functions mostly involve catalysis, ion transport, and ribonucleoprotein complex assembly. In turn, the fraction of yeast genes whose traceability is not sufficient to infer their presence in last universal common ancestor is enriched for regulatory functions. Computing the traceabilities of genes that have been experimentally characterized as being essential for a self-replicating cell reveals that many of the genes that lack orthologs outside bacteria have low traceability. This leaves open whether their orthologs in the eukaryotic and archaeal domains have been overlooked. Looking at the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and nondetection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks. "protTrace," a software tool for computing evolutionary traceability, is freely available at https://github.com/BIONF/protTrace.git; last accessed February 10, 2019.
In solid tumors, tumor‐associated macrophages (TAMs) commonly accumulate within hypoxic areas. Adaptations to such environments evoke transcriptional changes by the hypoxia‐inducible factors (HIFs). While HIF‐1α is ubiquitously expressed, HIF‐2α appears tissue‐specific with consequences of HIF‐2α expression in TAMs only being poorly characterized. An E0771 allograft breast tumor model revealed faster tumor growth in myeloid HIF‐2α knockout (HIF‐2αLysM−/−) compared with wildtype (wt) mice. In an RNA‐sequencing approach of FACS sorted wt and HIF‐2α LysM−/− TAMs, serine protease inhibitor, Kunitz type‐1 ( Spint1) emerged as a promising candidate for HIF‐2α‐dependent regulation. We validated reduced Spint1 messenger RNA expression and concomitant Spint1 protein secretion under hypoxia in HIF‐2α‐deficient bone marrow–derived macrophages (BMDMs) compared with wt BMDMs. In line with the physiological function of Spint1 as an inhibitor of hepatocyte growth factor (HGF) activation, supernatants of hypoxic HIF‐2α knockout BMDMs, not containing Spint1, were able to release proliferative properties of inactive pro‐HGF on breast tumor cells. In contrast, hypoxic wt BMDM supernatants containing abundant Spint1 amounts failed to do so. We propose that Spint1 contributes to the tumor‐suppressive function of HIF‐2α in TAMs in breast tumor development.
Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. Orthologous genes that are detected across the full diversity of contemporary life allow reconstructing the gene set of LUCA, the last universal common ancestor. These genes presumably represent the functional repertoire common to – and necessary for – all living organisms. Design of artificial life has the potential to test this. Recently, a minimal gene (MG) set for a self-replicating cell was determined experimentally, and a surprisingly high number of genes have unknown functions and are not represented in LUCA. However, as similarity between orthologs decays with time, it becomes insufficient to infer common ancestry, leaving ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the evolutionary traceability, together with the software protTrace, that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. We show that the LUCA set comprises only high-traceable proteins most of which have catalytic functions. We further show that proteins in the MG set lacking orthologs outside bacteria mostly have low traceability, leaving open whether their eukaryotic orthologs have just been overlooked. On the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and non-detection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks.