Immune checkpoint inhibitor-related pneumonitis: research advances in prediction and management.

The advent of immune-checkpoint inhibitors (ICIs) has revolutionized the treatment of malignant solid tumors in the last decade, producing lasting benefits in a subset of patients. However, unattended excessive immune responses may lead to immune-related adverse events (irAEs). IrAEs can manifest in different organs within the body, with pulmonary toxicity commonly referred to as immune checkpoint inhibitor-related pneumonitis (CIP). The CIP incidence remains high and is anticipated to rise further as the therapeutic indications for ICIs expand to encompass a wider range of malignancies. The diagnosis and treatment of CIP is difficult due to the large individual differences in its pathogenesis and severity, and severe CIP often leads to a poor prognosis for patients. This review summarizes the current state of clinical research on the incidence, risk factors, predictive biomarkers, diagnosis, and treatment for CIP, and we address future directions for the prevention and accurate prediction of CIP.

The genomic footprint of whaling and isolation in fin whale populations.

Twentieth century industrial whaling pushed several species to the brink of extinction, with fin whales being the most impacted. However, a small, resident population in the Gulf of California was not targeted by whaling. Here, we analyzed 50 whole-genomes from the Eastern North Pacific (ENP) and Gulf of California (GOC) fin whale populations to investigate their demographic history and the genomic effects of natural and human-induced bottlenecks. We show that the two populations diverged ~16,000 years ago, after which the ENP population expanded and then suffered a 99% reduction in effective size during the whaling period. In contrast, the GOC population remained small and isolated, receiving less than one migrant per generation. However, this low level of migration has been crucial for maintaining its viability. Our study exposes the severity of whaling, emphasizes the importance of migration, and demonstrates the use of genome-based analyses and simulations to inform conservation strategies.

Evolution of the Mutation Spectrum Across a Mammalian Phylogeny.

Although evolutionary biologists have long theorized that variation in DNA repair efficacy might explain some of the diversity of lifespan and cancer incidence across species, we have little data on the variability of normal germline mutagenesis outside of humans. Here, we shed light on the spectrum and etiology of mutagenesis across mammals by quantifying mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k-mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clock-like mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the 1-mer spectrum's phylogenetic signal in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.

"Evolution of the mutation spectrum across a mammalian phylogeny".

Little is known about how the spectrum and etiology of germline mutagenesis might vary among mammalian species. To shed light on this mystery, we quantify variation in mutational sequence context biases using polymorphism data from thirteen species of mice, apes, bears, wolves, and cetaceans. After normalizing the mutation spectrum for reference genome accessibility and k -mer content, we use the Mantel test to deduce that mutation spectrum divergence is highly correlated with genetic divergence between species, whereas life history traits like reproductive age are weaker predictors of mutation spectrum divergence. Potential bioinformatic confounders are only weakly related to a small set of mutation spectrum features. We find that clocklike mutational signatures previously inferred from human cancers cannot explain the phylogenetic signal exhibited by the mammalian mutation spectrum, despite the ability of these clocklike signatures to fit each species' 3-mer spectrum with high cosine similarity. In contrast, parental aging signatures inferred from human de novo mutation data appear to explain much of the mutation spectrum's phylogenetic signal when fit to non-context-dependent mutation spectrum data in combination with a novel mutational signature. We posit that future models purporting to explain the etiology of mammalian mutagenesis need to capture the fact that more closely related species have more similar mutation spectra; a model that fits each marginal spectrum with high cosine similarity is not guaranteed to capture this hierarchy of mutation spectrum variation among species.

Soil Microbial Community Composition and Tolerance to Contaminants in an Urban Brownfield Site.

Brownfields are unused sites that contain hazardous substances due to previous commercial or industrial use. The sites are inhospitable for many organisms, but some fungi and microbes can tolerate and thrive in the nutrient-depleted and contaminated soils. However, few studies have characterized the impacts of long-term contamination on soil microbiome composition and diversity at brownfields. This study focuses on an urban brownfield-a former rail yard in Los Angeles that is contaminated with heavy metals, volatile organic compounds, and petroleum-derived pollutants. We anticipate that heavy metals and organic pollutants will shape soil microbiome diversity and that several candidate fungi and bacteria will be tolerant to the contaminants. We sequence three gene markers (16S ribosomal RNA, 18S ribosomal RNA, and the fungal internal transcribed spacer (FITS)) in 55 soil samples collected at five depths to (1) profile the composition of the soil microbiome across depths; (2) determine the extent to which hazardous chemicals predict microbiome variation; and (3) identify microbial taxonomic groups that may metabolize these contaminants. Detected contaminants in the samples included heavy metals, petroleum hydrocarbons, polycyclic aromatic hydrocarbons, and volatile organic compounds. Bacterial, eukaryotic, and fungal communities all varied with depth and with concentrations of arsenic, chromium, cobalt, and lead. 18S rRNA microbiome richness and fungal richness were positively correlated with lead and cobalt levels, respectively. Furthermore, bacterial Paenibacillus and Iamia, eukaryotic Actinochloris, and fungal Alternaria were enriched in contaminated soils compared to uncontaminated soils and represent taxa of interest for future bioremediation research. Based on our results, we recommend incorporating DNA-based multi-marker microbial community profiling at multiple sites and depths in brownfield site assessment standard methods and restoration.

A centenary tale: population genetic insights into the introduction history of the oriental fire-bellied toad (Bombina orientalis) in Beijing.

BACKGROUND: The successful establishment of a species population following a single introduction of a few individuals to a non-native area has been limited. Nevertheless, the oriental fire-bellied toad (Bombina orientalis) population in Beijing is purportedly descended from a single introduction of about 200 individuals translocated from Yantai, Shandong Province, China, in 1927. RESULTS: To resolve the introduction process and to understand the genetic consequences since that introduction approximately 90 years ago, we investigated the population's genetic diversity and structure using 261 toads from Beijing and two native Shandong populations and inferred the species' introduction history using simulation-based approaches. Analysis of mitochondrial DNA (mtDNA) sequences showed the two haplotypes found in Beijing nested within Yantai haplotypes, thus corroborating the historical record of the translocation source. The mtDNA and 11 nuclear microsatellite markers revealed both considerably lower genetic diversity in Beijing than in the source population and strong genetic differentiation between them. Although the current census population in Beijing may be in the range of a few thousand, the effective population size was estimated at only 20-57. Simulations also suggest that this population may have descended from 40-60 founders. CONCLUSIONS: The Beijing population's genetic patterns were consistent with the consequences of a severe bottleneck during introduction followed by genetic drift. The introduction trajectory constructed for this B. orientalis population reveals the genetic footprints of a small population sustained in isolation for nearly a century. Our results provide an intriguing example of establishment success from limited founders and may inform ex situ conservation efforts as well as the management of biological invasions.

A Reference Genome Assembly of the Bobcat, Lynx rufus.

The bobcat (Lynx rufus) is a medium-sized carnivore well adapted to various environments and an indicator species for landscape connectivity. It is one of the 4 species within the extant Lynx genus in the family Felidae. Because of its broad geographic distribution and central role in food webs, the bobcat is important for conservation. Here we present a high-quality de novo genome assembly of a male bobcat located in Mendocino County, CA, as part of the California Conservation Genomics Project (CCGP). The assembly was generated using the standard CCGP pipeline from a combination of Omni-C and HiFi technologies. The primary assembly comprises 76 scaffolds spanning 2.4 Gb, represented by a scaffold N50 of 142 Mb, a contig N50 of 66.2 Mb, and a BUSCO completeness score of 95.90%. The bobcat genome will be an important resource for the effective management and conservation of this species and comparative genomics exploration.

The Role of Gut Microbiota in Lung Cancer: From Carcinogenesis to Immunotherapy.

The influence of microbiota on host health and disease has attracted adequate attention, and gut microbiota components and microbiota-derived metabolites affect host immune homeostasis locally and systematically. Some studies have found that gut dysbiosis, disturbance of the structure and function of the gut microbiome, disrupts pulmonary immune homeostasis, thus leading to increased disease susceptibility; the gut-lung axis is the primary cross-talk for this communication. Gut dysbiosis is involved in carcinogenesis and the progression of lung cancer through genotoxicity, systemic inflammation, and defective immunosurveillance. In addition, the gut microbiome harbors the potential to be a novel biomarker for predicting sensitivity and adverse reactions to immunotherapy in patients with lung cancer. Probiotics and fecal microbiota transplantation (FMT) can enhance the efficacy and depress the toxicity of immune checkpoint inhibitors by regulating the gut microbiota. Although current studies have found that gut microbiota closely participates in the development and immunotherapy of lung cancer, the mechanisms require further investigation. Therefore, this review aims to discuss the underlying mechanisms of gut microbiota influencing carcinogenesis and immunotherapy in lung cancer and to provide new strategies for governing gut microbiota to enhance the prevention and treatment of lung cancer.

Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California.

Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi-scalar community-level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel-2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.