metabolic evolution
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mBio ◽  
2021 ◽  
Author(s):  
Aidan Dmitriev ◽  
Xingru Chen ◽  
Elyse Paluscio ◽  
Amelia C. Stephens ◽  
Srijon K. Banerjee ◽  
...  

Pathogens must evolve virulence potential to improve transmission to new hosts as well as evolve metabolically to thrive within their current host. Staphylococcus aureus has achieved both of these, and here, we show that one such metabolic adaptation was the expansion of the Rex regulon. First, it affords S. aureus with efficient respiration-independent growth critical to surviving the inflammatory environment replete with respiration-inhibiting immune radicals.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meng Nie ◽  
Ke Yao ◽  
Xinsheng Zhu ◽  
Na Chen ◽  
Nan Xiao ◽  
...  

AbstractMetabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies.


2021 ◽  
Author(s):  
Eiichiro Ono ◽  
Kohki Shimizu ◽  
Jun Murata ◽  
Akira Shiraishi ◽  
Ryusuke Yokoyama ◽  
...  

Abstract Recent genomic studies of parasitic plants have revealed that there are numerous footprints indicative of horizontal gene transfer (HGT) to the parasites from their host plants. However, the molecular mechanisms and biological impacts of this phenomenon have remained largely unknown. Here, we made the striking observation that two parasitic dodders, Cuscuta campestris and C. australis, have functional homologues of Si_CYP81Q1, which encodes piperitol/sesamin synthase (PSS) in the phylogenetically remote plant Sesamum indicum (sesame). The apparent lack of sequence similarity between the regions flanking PSS in Sesamum and Cuscuta spp. suggests the occurrence of HGT tightly associated with the PSS gene. Upon parasitism, C. campestris induced expression of the host Si_CYP81Q1 at the parasitic interface and mature and intron-retained Si_CYP81Q1 mRNA was transferred to C. campestris, suggesting that CYP81Q1 was translocated via RNA-mediated HGT. Thus, parasitism-evoked HGT might have had an unexpected role in the metabolic evolution of plants.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Misty R. Riddle ◽  
Ariel Aspiras ◽  
Fleur Damen ◽  
Suzanne McGaugh ◽  
Julius A. Tabin ◽  
...  

Abstract Background Despite a longstanding interest in understanding how animals adapt to environments with limited nutrients, we have incomplete knowledge of the genetic basis of metabolic evolution. The Mexican tetra, Astyanax mexicanus, is a species of fish that consists of two morphotypes; eyeless cavefish that have adapted to a low-nutrient cave environment, and ancestral river-dwelling surface fish with abundant access to nutrients. Cavefish have evolved altered blood sugar regulation, starvation tolerance, increased fat accumulation, and superior body condition. To investigate the genetic basis of cavefish metabolic evolution we carried out a quantitative trait loci (QTL) analysis in surface/cave F2 hybrids. We genetically mapped seven metabolism-associated traits in hybrids that were challenged with a nutrient restricted diet. Results We found that female F2 hybrids are bigger than males and have a longer hindgut, bigger liver, and heavier gonad, even after correcting for fish size. Although there is no difference between male and female blood sugar level, we found that high blood sugar is associated with weight gain in females and lower body weight and fat level in males. We identified a significant QTL associated with 24-h-fasting blood glucose level with the same effect in males and females. Differently, we identified sex-independent and sex-dependent QTL associated with fish length, body condition, liver size, hindgut length, and gonad weight. We found that some of the genes within the metabolism QTL display evidence of non-neutral evolution and are likely to be under selection. Furthermore, we report predicted nonsynonymous changes to the cavefish coding sequence of these genes. Conclusions Our study reveals previously unappreciated genomic regions associated with blood glucose regulation, body condition, gonad size, and internal organ morphology. In addition, we find an interaction between sex and metabolism-related traits in A. mexicanus. We reveal coding changes in genes that are likely under selection in the low-nutrient cave environment, leading to a better understanding of the genetic basis of metabolic evolution.


2020 ◽  
Vol 30 (24) ◽  
pp. 4984-4988.e4 ◽  
Author(s):  
Rachael Evans ◽  
Andrew P. Beckerman ◽  
Rosanna C.T. Wright ◽  
Simon McQueen-Mason ◽  
Neil C. Bruce ◽  
...  

2020 ◽  
Author(s):  
Francesco Cicone ◽  
Luciano Carideo ◽  
Claudia Scaringi ◽  
Andrea Romano ◽  
Marcelo Mamede ◽  
...  

Abstract Background The evolution of radiation necrosis (RN) varies depending on the combination of radionecrotic tissue and active tumor cells. In this study, we characterized the long-term metabolic evolution of RN by sequential PET/CT imaging with 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine (F-DOPA) in patients with brain metastases following stereotactic radiosurgery (SRS). Methods Thirty consecutive patients with 34 suspected radionecrotic brain metastases following SRS repeated F-DOPA PET/CT every 6 months or yearly in addition to standard MRI monitoring. Diagnoses of local progression (LP) or RN were confirmed histologically or by clinical follow-up. Semi-quantitative parameters of F-DOPA uptake were extracted at different time points, and their diagnostic performances were compared with those of corresponding contrast-enhanced MRI. Results Ninety-nine F-DOPA PET scans were acquired over a median period of 18 (range: 12–66) months. Median follow-up from the baseline F-DOPA PET/CT was 48 (range 21–95) months. Overall, 24 (70.6%) and 10 (29.4%) lesions were classified as RN and LP, respectively. LP occurred after a median of 18 (range: 12–30) months from baseline PET. F-DOPA tumor-to-brain ratio (TBR) and relative standardized uptake value (rSUV) increased significantly over time in LP lesions, while remaining stable in RN lesions. The parameter showing the best diagnostic performance was rSUV (accuracy = 94.1% for the optimal threshold of 1.92). In contrast, variations of the longest tumor dimension measured on contrast-enhancing MRI did not distinguish between RN and LP. Conclusion F-DOPA PET has a high diagnostic accuracy for assessing the long-term evolution of brain metastases following SRS.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Elis Newham ◽  
Pamela G. Gill ◽  
Philippa Brewer ◽  
Michael J. Benton ◽  
Vincent Fernandez ◽  
...  

Abstract Despite considerable advances in knowledge of the anatomy, ecology and evolution of early mammals, far less is known about their physiology. Evidence is contradictory concerning the timing and fossil groups in which mammalian endothermy arose. To determine the state of metabolic evolution in two of the earliest stem-mammals, the Early Jurassic Morganucodon and Kuehneotherium, we use separate proxies for basal and maximum metabolic rate. Here we report, using synchrotron X-ray tomographic imaging of incremental tooth cementum, that they had maximum lifespans considerably longer than comparably sized living mammals, but similar to those of reptiles, and so they likely had reptilian-level basal metabolic rates. Measurements of femoral nutrient foramina show Morganucodon had blood flow rates intermediate between living mammals and reptiles, suggesting maximum metabolic rates increased evolutionarily before basal metabolic rates. Stem mammals lacked the elevated endothermic metabolism of living mammals, highlighting the mosaic nature of mammalian physiological evolution.


2020 ◽  
Vol 74 (1) ◽  
pp. 291-313 ◽  
Author(s):  
Timothy Y. James ◽  
Jason E. Stajich ◽  
Chris Todd Hittinger ◽  
Antonis Rokas

In this review, we discuss the current status and future challenges for fully elucidating the fungal tree of life. In the last 15 years, advances in genomic technologies have revolutionized fungal systematics, ushering the field into the phylogenomic era. This has made the unthinkable possible, namely access to the entire genetic record of all known extant taxa. We first review the current status of the fungal tree and highlight areas where additional effort will be required. We then review the analytical challenges imposed by the volume of data and discuss methods to recover the most accurate species tree given the sea of gene trees. Highly resolved and deeply sampled trees are being leveraged in novel ways to study fungal radiations, species delimitation, and metabolic evolution. Finally, we discuss the critical issue of incorporating the unnamed and uncultured dark matter taxa that represent the vast majority of fungal diversity.


2020 ◽  
Author(s):  
Marcelo Otero ◽  
Silvina Sarno ◽  
Sofía Acebedo ◽  
Javier Alberto Ramirez

Chemoinformatic tools have been widely used to analyze the properties of large sets of natural compounds, mostly in the context of drug discovery. Nevertheless, fewer reports have aimed to answer basic biological questions. In this work, we have applied unsupervised machine learning techniques to assess the diversity and complexity of a set of natural steroids by characterizing them through simple topological and physicochemical molecular descriptors. As a most noteworthy result, these properties, derived from the molecular graphs of the compounds, are closely related to their biological functions and to their biosynthetic origins. Moreover, a trend paralleling diversification of the properties and metabolic evolution can be established, demonstrating the potential contribution of these computational approaches to better understanding the vast wealth of natural products.


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