Spatial and temporal variation in New Hampshire bat diets.

Insectivorous bats consume a diverse array of arthropod prey, with diets varying by bat species, sampling location, and season. North American bat diets remain incompletely described, which is concerning at a time when many bat and insect populations appear to be declining. Understanding the variability in foraging is thus an essential component for effective bat conservation. To comprehensively evaluate local foraging, we assessed the spatial and temporal variability in prey consumed by the little brown bat, Myotis lucifugus, in New Hampshire, USA. We collected bat guano samples from 20 sites over 2 years and analyzed sequence data for 899 of these samples using a molecular metabarcoding approach targeting the cytochrome oxidase I subunit (COI) gene. Some prey items were broadly shared across locations and sampling dates, with the most frequently detected arthropod orders broadly similar to previous morphological and molecular analyses; at least one representative sequence variant was assigned to Coleoptera in 92% of samples, with other frequently detected orders including Diptera (73%), Lepidoptera (65%), Trichoptera (38%), and Ephemeroptera (32%). More specifically, two turf and forest pests were routinely detected: white grubs in the genus Phyllophaga (50%), and the Asiatic Garden beetle, Maladera castanea (36%). Despite the prevalence of a few taxa shared among many samples and distinct seasonal peaks in consumption of specific arthropods, diet composition varied both temporally and spatially. However, species richness did not strongly vary indicating consumption of a broad diversity of taxa throughout the summer. These data characterize little brown bats as flexible foragers adept at consuming a broad array of locally available prey resources.

RESCRIPt: Reproducible sequence taxonomy reference database management.

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses.

Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates compared to traditional clustering methods, although these differences are largely mitigated by removing low-abundance sequence variants. We also found that available reference datasets from GenBank and BOLD for the animal marker gene cytochrome oxidase I (COI) can be complementary, and we discuss methods to improve existing databases to include versioned releases. Taxonomic classification methods can dramatically affect results. For example, the commonly used Barcode of Life Database (BOLD) Classification API assigned fewer names to samples from order through species levels using both a mock community and bat guano samples compared to all other classifiers (vsearch-SINTAX and q2-feature-classifier's BLAST + LCA, VSEARCH + LCA, and Naive Bayes classifiers). The lack of consensus on bioinformatics best practices limits comparisons among studies and may introduce biases. Our work suggests that biological mock communities offer a useful standard to evaluate the myriad computational decisions impacting animal metabarcoding accuracy. Further, these comparisons highlight the need for continual evaluations as new tools are adopted to ensure that the inferences drawn reflect meaningful biology instead of digital artifacts.

The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise.

The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication," 2) "Methodological and analytical advancements," 3) "Translation into practice," 4) "Integrating landscape ecology and genomics," and 5) "Emerging new questions." Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.

A novel CRISPR/Cas9 associated technology for sequence-specific nucleic acid enrichment.

Massively parallel sequencing technologies have made it possible to generate large quantities of sequence data. However, as research-associated information is transferred into clinical practice, cost and throughput constraints generally require sequence-specific targeted analyses. Therefore, sample enrichment methods have been developed to meet the needs of clinical sequencing applications. However, current amplification and hybrid capture enrichment methods are limited in the contiguous length of sequences for which they are able to enrich. PCR based amplification also loses methylation data and other native DNA features. We have developed a novel technology (Negative Enrichment) where we demonstrate targeting long (>10 kb) genomic regions of interest. We use the specificity of CRISPR-Cas9 single guide RNA (Cas9/sgRNA) complexes to define 5' and 3' termini of sequence-specific loci in genomic DNA, targeting 10 to 36 kb regions. The complexes were found to provide protection from exonucleases, by protecting the targeted sequences from degradation, resulting in enriched, double-strand, non-amplified target sequences suitable for next-generation sequencing library preparation or other downstream analyses.

There and back again: consequences of biofilm specialization under selection for dispersal.

Experimental evolution paired with modern sequencing can be a powerful approach to identify the mechanisms by which bacteria adapt to discrete environmental conditions found in nature or during infections. We used this approach to identify mechanisms enabling biofilm specialists of the opportunistic respiratory pathogen Burkholderia cenocepacia to regain planktonic fitness. Seven mutants producing wrinkly (W) small-colony variants by mutations in the wrinkly-spreader operon (wsp) cluster, but with varying duration of biofilm adaptation, served as ancestors of this experiment. Following planktonic growth, each W ancestor produced smooth (S) mutants with distinct fitness effects across planktonic, biofilm, and dispersal-phase environments. The causes of the S phenotype traced to mutations in three gene clusters: wsp, Bcen2424_1436, an uncharacterized two-component transcriptional regulator which appears to be critical for wsp signaling, and a cohort of genes involved in polysaccharide synthesis. The genetic pathway from W to S also associated with evolutionary history in the biofilm environment. W mutants isolated from long-term biofilm selection usually produced S types via secondary wsp mutations, whereas S types evolved from less adapted W ancestors by a wider scope of mutations. These different genetic pathways to suppress the W phenotype suggest that prolonged biofilm adaptation limits routes to subsequent planktonic adaptation, despite common initial mechanisms of biofilm adaptation. More generally, experimental evolution can be used as a nuanced screen for gain-of-function mutations in multiple conditions that illustrate tensions that bacteria may face in changing environments or hosts.

Developmental expression patterns of the zebrafish small heat shock proteins.

Small heat shock proteins (sHSPs), or alpha-crystallins, are low-molecular weight proteins found in every kingdom and nearly every species examined to date. Many, if not all, sHSPs act as molecular chaperones. Several also have functions independent of their chaperone activity, and at least a few are expressed in specific spatiotemporal patterns during embryonic and/or juvenile stages, suggesting specific roles during development. To date, however, no one has systematically characterized the expression patterns of all of the sHSPs during development in any organism. We have characterized the normal heat shock-induced expression patterns of all 13 zebrafish sHSPs during development. Seven of the sHSPs are expressed in a tissue-specific manner during development, and five are upregulated by heat shock. The results of these studies provide a foundation for analysis of sHSP function during normal development and their roles in protecting cells from the effects environmental stressors.