Nectar-feeding bats and birds show parallel molecular adaptations in sugar metabolism enzymes

Diverse signatures of convergent evolution in cactus-associated yeasts

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently approximately 17 times. Using a machine learning-based approach, we further found that cactophily can be predicted with 76% accuracy from both functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which we found to be likely associated with altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved independently through disparate molecular mechanisms. Notably, we found that multiple cactophilic species and their close relatives have been reported as emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-might preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high-throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

High sugar diet alters immune function and the gut microbiome in juvenile green iguanas (Iguana iguana)

The present work aimed to study whether a high sugar diet can alter immune responses and the gut microbiome in green iguanas. Thirty-six iguanas were split into four treatment groups using a 2×2 design. Iguanas received either a sugar-supplemented diet or a control diet, and either a lipopolysaccharide (LPS) injection or a phosphate-buffered saline (PBS) injection. Iguanas were given their respective diet treatment through the entire study (∼3 months) and received a primary immune challenge 1 and 2 months into the experiment. Blood samples and cloacal swabs were taken at various points in the experiment and used to measure changes in the immune system (bacterial killing ability, lysis and agglutination scores, LPS-specific IgY concentrations), and alterations in the gut microbiome. We found that a sugar diet reduces bacterial killing ability following an LPS challenge, and sugar and the immune challenge temporarily alters gut microbiome composition while reducing alpha diversity. Although sugar did not directly reduce lysis and agglutination following the immune challenge, the change in these scores over a 24-h period following an immune challenge was more drastic (it decreased) relative to the control diet group. Moreover, sugar increased constitutive agglutination outside of the immune challenges (i.e. pre-challenge levels). In this study, we provide evidence that a high sugar diet affects the immune system of green iguanas (in a disruptive manner) and alters the gut microbiome.

Diverse signatures of convergent evolution in cacti-associated yeasts

Many distantly related organisms have convergently evolved traits and lifestyles that enable them to live in similar ecological environments. However, the extent of phenotypic convergence evolving through the same or distinct genetic trajectories remains an open question. Here, we leverage a comprehensive dataset of genomic and phenotypic data from 1,049 yeast species in the subphylum Saccharomycotina (Kingdom Fungi, Phylum Ascomycota) to explore signatures of convergent evolution in cactophilic yeasts, ecological specialists associated with cacti. We inferred that the ecological association of yeasts with cacti arose independently ~17 times. Using machine-learning, we further found that cactophily can be predicted with 76% accuracy from functional genomic and phenotypic data. The most informative feature for predicting cactophily was thermotolerance, which is likely associated with duplication and altered evolutionary rates of genes impacting the cell envelope in several cactophilic lineages. We also identified horizontal gene transfer and duplication events of plant cell wall-degrading enzymes in distantly related cactophilic clades, suggesting that putatively adaptive traits evolved through disparate molecular mechanisms. Remarkably, multiple cactophilic lineages and their close relatives are emerging human opportunistic pathogens, suggesting that the cactophilic lifestyle-and perhaps more generally lifestyles favoring thermotolerance-may preadapt yeasts to cause human disease. This work underscores the potential of a multifaceted approach involving high throughput genomic and phenotypic data to shed light onto ecological adaptation and highlights how convergent evolution to wild environments could facilitate the transition to human pathogenicity.

Next Generation Sequencing Revolutionizes Organismal Biology Research in Bats

The advent of next generation sequencing technologies (NGS) has greatly accelerated our understanding of critical aspects of organismal biology from non-model organisms. Bats form a particularly interesting group in this regard, as genomic data have helped unearth a vast spectrum of idiosyncrasies in bat genomes associated with bat biology, physiology, and evolution. Bats are important bioindicators and are keystone species to many eco-systems. They often live in proximity to humans and are frequently associated with emerging infectious diseases, including the COVID-19 pandemic. Nearly four dozen bat genomes have been published to date, ranging from drafts to chromosomal level assemblies. Genomic investigations in bats have also become critical towards our understanding of disease biology and host-pathogen coevolution. In addition to whole genome sequencing, low coverage genomic data like reduced representation libraries, resequencing data, etc. have contributed significantly towards our understanding of the evolution of natural populations, and their responses to climatic and anthropogenic perturbations. In this review, we discuss how genomic data have enhanced our understanding of physiological adaptations in bats (particularly related to ageing, immunity, diet, etc.), pathogen discovery, and host pathogen co-evolution. In comparison, the application of NGS towards population genomics, conservation, biodiversity assessment, and functional genomics has been appreciably slower. We reviewed the current areas of focus, identifying emerging topical research directions and providing a roadmap for future genomic studies in bats.

How hummingbirds hover: Natural selection for energetics of hovering flight

Osipova et al.¹ recently identified an inactivating gene mutation that contributed to the evolution of the hummingbird species by increasing flux of pathways for energy production that are necessary for the unique ability for hovering flight. Lessons from the natural selection for this mutation are applied to physiology and medicine.

A role of cytoplasmic p53 in the regulation of metabolism shown by bat-mimicking p53 NLS mutant mice

The transcription factor p53 suppresses tumorigenesis via a wide-ranging, concerted set of functions. Although several studies have identified cytoplasmic, transcription-independent functions of p53, the biological relevance of these activities has not been fully elucidated, particularly in vivo. Here, we generated a mouse model with a p53^K316P mutation, which mimics a naturally occurring p53 nuclear localization signal (NLS) change observed in bat species. We find that the p53^K316P mutation increases cytoplasmic localization of p53 and promotes a pleiotropic metabolic phenotype that includes increased adiposity, increased de novo lipogenesis, and decreased lactate generation. Mechanistic studies show that, independent of its transactivation function, p53^K316P interacts with lactate dehydrogenase B (LDHB) and alters the composition and enzymatic activities of LDH complex favoring pyruvate generation and hindering lactate production. Overall, the study identifies a role for cytoplasmic p53 in the regulation of metabolism that favors energy generation and storage.

Loss of a gluconeogenic muscle enzyme contributed to adaptive metabolic traits in hummingbirds

Hummingbirds possess distinct metabolic adaptations to fuel their energy-demanding hovering flight, but the underlying genomic changes are largely unknown. Here, we generated a chromosome-level genome assembly of the long-tailed hermit and screened for genes that have been specifically inactivated in the ancestral hummingbird lineage. We discovered that FBP2 (fructose-bisphosphatase 2), which encodes a gluconeogenic muscle enzyme, was lost during a time period when hovering flight evolved. We show that FBP2 knockdown in an avian muscle cell line up-regulates glycolysis and enhances mitochondrial respiration, coincident with an increased mitochondria number. Furthermore, genes involved in mitochondrial respiration and organization have up-regulated expression in hummingbird flight muscle. Together, these results suggest that FBP2 loss was likely a key step in the evolution of metabolic muscle adaptations required for true hovering flight.

Multi-omics analysis reveals the pathogenesis of db/db mice diabetic kidney disease and the treatment mechanisms of multi-bioactive compounds combination from Salvia miltiorrhiza

Diabetic kidney disease (DKD) is a common diabetic complication. Salvia miltiorrhiza has significant therapeutic effects on diabetes complications, although the mechanism remains unclear. Here, biochemical indicators and pathological changes were used to screen out the optimal Salvia miltiorrhiza multi-bioactive compounds combination. Metabolomics, transcriptomics and proteomics were used to explore the pathogenesis of DKD. RT-PCR and parallel reaction monitoring targeted quantitative proteome analysis were utilized to investigate treatment mechanisms of the optimal Salvia miltiorrhiza multi-bioactive compounds combination. The db/db mice showed biochemical abnormalities and renal lesions. The possible metabolic pathways were steroid hormone biosynthesis and sphingolipid metabolism. The 727 differential genes found in transcriptomics were associated with biochemical indicators via gene network to finally screen 11 differential genes, which were mainly key genes of TGF-β/Smad and PI3K/Akt/FoxO signaling pathways. Salvia miltiorrhiza multi-bioactive compounds combination could significantly regulate the Egr1, Pik3r3 and Col1a1 genes. 11 differentially expressed proteins involved in the two pathways were selected, of which 9 were significantly altered in db/db mice compared to db/m mice. Salvia miltiorrhiza multi-bioactive compounds combination could callback Q9DBM2, S4R1W1, Q91Y97, P47738, A8DUK4, and A2ARV4. In summary, Salvia miltiorrhiza multi-bioactive compounds combination may ameliorate kidney injury in diabetes through regulation of TGF-β/Smad and PI3K/Akt/FoxO signaling pathways.