Preclinical evaluation and first-in-dog clinical trials of PBMC-expanded natural killer cells for adoptive immunotherapy in dogs with cancer.

BACKGROUND: Natural killer (NK) cells are cytotoxic cells capable of recognizing heterogeneous cancer targets without prior sensitization, making them promising prospects for use in cellular immunotherapy. Companion dogs develop spontaneous cancers in the context of an intact immune system, representing a valid cancer immunotherapy model. Previously, CD5 depletion of peripheral blood mononuclear cells (PBMCs) was used in dogs to isolate a CD5dim-expressing NK subset prior to co-culture with an irradiated feeder line, but this can limit the yield of the final NK product. This study aimed to assess NK activation, expansion, and preliminary clinical activity in first-in-dog clinical trials using a novel system with unmanipulated PBMCs to generate our NK cell product. METHODS: Starting populations of CD5-depleted cells and PBMCs from healthy beagle donors were co-cultured for 14 days, phenotype, cytotoxicity, and cytokine secretion were measured, and samples were sequenced using the 3'-Tag-RNA-Seq protocol. Co-cultured human PBMCs and NK-isolated cells were also sequenced for comparative analysis. In addition, two first-in-dog clinical trials were performed in dogs with melanoma and osteosarcoma using autologous and allogeneic NK cells, respectively, to establish safety and proof-of-concept of this manufacturing approach. RESULTS: Calculated cell counts, viability, killing, and cytokine secretion were equivalent or higher in expanded NK cells from canine PBMCs versus CD5-depleted cells, and immune phenotyping confirmed a CD3-NKp46+ product from PBMC-expanded cells at day 14. Transcriptomic analysis of expanded cell populations confirmed upregulation of NK activation genes and related pathways, and human NK cells using well-characterized NK markers closely mirrored canine gene expression patterns. Autologous and allogeneic PBMC-derived NK cells were successfully expanded for use in first-in-dog clinical trials, resulting in no serious adverse events and preliminary efficacy data. RNA sequencing of PBMCs from dogs receiving allogeneic NK transfer showed patient-unique gene signatures with NK gene expression trends in response to treatment. CONCLUSIONS: Overall, the use of unmanipulated PBMCs appears safe and potentially effective for canine NK immunotherapy with equivalent to superior results to CD5 depletion in NK expansion, activation, and cytotoxicity. Our preclinical and clinical data support further evaluation of this technique as a novel platform for optimizing NK immunotherapy in dogs.

Biogeographic distribution of five Antarctic cyanobacteria using large-scale k-mer searching with sourmash branchwater.

Cyanobacteria form diverse communities and are important primary producers in Antarctic freshwater environments, but their geographic distribution patterns in Antarctica and globally are still unresolved. There are however few genomes of cultured cyanobacteria from Antarctica available and therefore metagenome-assembled genomes (MAGs) from Antarctic cyanobacteria microbial mats provide an opportunity to explore distribution of uncultured taxa. These MAGs also allow comparison with metagenomes of cyanobacteria enriched communities from a range of habitats, geographic locations, and climates. However, most MAGs do not contain 16S rRNA gene sequences, making a 16S rRNA gene-based biogeography comparison difficult. An alternative technique is to use large-scale k-mer searching to find genomes of interest in public metagenomes. This paper presents the results of k-mer based searches for 5 Antarctic cyanobacteria MAGs from Lake Fryxell and Lake Vanda, assigned the names Phormidium pseudopriestleyi FRX01, Microcoleus sp. MP8IB2.171, Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, and Leptolyngbyaceae cyanobacterium MP9P1.79 in 498,942 unassembled metagenomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The Microcoleus sp. MP8IB2.171 MAG was found in a wide variety of environments, the P. pseudopriestleyi MAG was found in environments with challenging conditions, the Leptolyngbyaceae cyanobacterium MP9P1.79 MAG was only found in Antarctica, and the Leptolyngbya sp. BulkMat.35 and Pseudanabaenaceae cyanobacterium MP8IB2.15 MAGs were found in Antarctic and other cold environments. The findings based on metagenome matches and global comparisons suggest that these Antarctic cyanobacteria have distinct distribution patterns ranging from locally restricted to global distribution across the cold biosphere and other climatic zones.

Pluripotency of a founding field: rebranding developmental biology.

The field of developmental biology has declined in prominence in recent decades, with off-shoots from the field becoming more fashionable and highly funded. This has created inequity in discovery and opportunity, partly due to the perception that the field is antiquated or not cutting edge. A 'think tank' of scientists from multiple developmental biology-related disciplines came together to define specific challenges in the field that may have inhibited innovation, and to provide tangible solutions to some of the issues facing developmental biology. The community suggestions include a call to the community to help 'rebrand' the field, alongside proposals for additional funding apparatuses, frameworks for interdisciplinary innovative collaborations, pedagogical access, improved science communication, increased diversity and inclusion, and equity of resources to provide maximal impact to the community.

Acipenserid herpesvirus 2 genome and partial validation of a qPCR for its detection in white sturgeon Acipenser transmontanus.

White sturgeon Acipenser transmontanus is the primary species used for caviar and sturgeon meat production in the USA. An important pathogen of white sturgeon is acipenserid herpesvirus 2 (AciHV-2). In this study, 4 archived isolates from temporally discrete natural outbreaks spanning the past 30 yr were sequenced via Illumina and Oxford Nanopore Technologies platforms. Assemblies of approximately 134 kb were obtained for each isolate, and the putative ATPase subunit of the terminase gene was selected as a potential quantitative PCR (qPCR) target based on sequence conservation among AciHV-2 isolates and low sequence homology with other important viral pathogens. The qPCR was repeatable and reproducible, with a linear dynamic range covering 5 orders of magnitude, an efficiency of approximately 96%, an R2 of 0.9872, and an analytical sensitivity of 103 copies per reaction after 35 cycles. There was no cross-reaction with other known viruses or closely related sturgeon species, and no inhibition by sturgeon DNA. Clinical accuracy was assessed from white sturgeon juveniles exposed to AciHV-2 by immersion. Viral culture (gold standard) and qPCR were in complete agreement for both cell culture negative and cell culture positive samples, indicating that this assay has 100% relative accuracy compared to cell culture during an active outbreak. The availability of a whole-genome sequence for AciHV-2 and a highly specific and sensitive qPCR assay for detection of AciHV-2 in white sturgeon lays a foundation for further studies on host-pathogen interactions while providing a specific and rapid test for AciHV-2 in captive and wild populations.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows.

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Missing a "Missing Self" Mechanism: Modeling and Detection of Ly49 Expression in Canine NK Cells.

NK cells are a key focus in immuno-oncology, based on their ability to eliminate malignant cells without prior sensitization. Dogs are valuable models for translational immunotherapy studies, especially for NK cells, where critical species differences exist between mice and humans. Given that the mechanism for recognition of "self" by canine NK cells is currently unknown, we sought to evaluate expression of Ly49 in canine NK cells using in silico and high-throughput techniques. We interrogated the identified polymorphism/mutation in canine Ly49 and assessed the potential impact on structure using computational modeling of three-dimensional protein structure and protein-protein docking of canine Ly49 with MHC class I (MHC-I). Bulk and single-cell RNA-sequencing analysis was performed to detect gene expression of Ly49/KLRA1 in resting and activated NK cells. Tertiary protein structure demonstrated significant structural similarity to the known murine system. Molecular docking of canine Ly49 with MHC-I was favorable, converging at a single low-energy conformation. RNA sequencing revealed expression of Ly49/KLRA1 in both resting and activated NK cells and demonstrated almost exclusive expression of the gene in the NK cluster at the single-cell level. Despite prior reports of a mutated, nonfunctional canine Ly49, our data support that the protein product is predicted to bind to MHC-I in a comparable conformation to the murine system and is expressed in canine NK cells with upregulation following activation. Taken together, these data suggest that Ly49 is capable of recognizing MHC-I and therefore regulating NK cell function in dogs.

Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets.

BACKGROUND: Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates. RESULTS: Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing. CONCLUSIONS: Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Making Common Fund data more findable: catalyzing a data ecosystem.

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.

Could a Focus on the "Why" of Taxonomy Help Taxonomy Better Respond to the Needs of Science and Society?

Genomics has put prokaryotic rank-based taxonomy on a solid phylogenetic foundation. However, most taxonomic ranks were set long before the advent of DNA sequencing and genomics. In this concept paper, we thus ask the following question: should prokaryotic classification schemes besides the current phylum-to-species ranks be explored, developed, and incorporated into scientific discourse? Could such alternative schemes provide better solutions to the basic need of science and society for which taxonomy was developed, namely, precise and meaningful identification? A neutral genome-similarity based framework is then described that could allow alternative classification schemes to be explored, compared, and translated into each other without having to choose only one as the gold standard. Classification schemes could thus continue to evolve and be selected according to their benefits and based on how well they fulfill the need for prokaryotic identification.

Microbial metabolites in the marine carbon cycle.

One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Comparative Immunogenomics of Canine Natural Killer Cells as Immunotherapy Target.

Natural killer (NK) cells are key effectors of the innate immune system, but major differences between human and murine NK cells have impeded translation. Outbred dogs offer an important link for studies of NK biology and immunotherapy. We analyzed gene expression of putative NK populations from healthy dogs and dogs with naturally-occurring cancers examining differential gene expression across multiple conditions, including steady-state, in vitro activation with cytokines and co-culture, and in vivo activation with inhaled IL-15 in dogs receiving IL-15 immunotherapy. We also compared dog, mouse and human CD3-NKp46+ NK cells using a novel orthologous transcriptome. Distinct transcriptional profiles between NK populations exist between conditions and in vitro versus in vivo treatments. In cross-species analysis, canine NK cells were globally more similar to human NK cells than mice. These data define canine NK cell gene expression under multiple conditions and across species, filling an important gap in translational NK studies.

Charting Shifts in Saccharomyces cerevisiae Gene Expression across Asynchronous Time Trajectories with Diffusion Maps.

During fermentation, Saccharomyces cerevisiae metabolizes sugars and other nutrients to obtain energy for growth and survival, while also modulating these activities in response to cell-environment interactions. Here, differences in S. cerevisiae gene expression were explored over a time course of fermentation and used to differentiate fermentations, using Pinot noir grapes from 15 unique sites. Data analysis was complicated by the fact that the fermentations proceeded at different rates, making a direct comparison of time series gene expression data difficult with conventional differential expression tools. This led to the development of a novel approach combining diffusion mapping with continuous differential expression analysis (termed DMap-DE). Using this method, site-specific deviations in gene expression were identified, including changes in gene expression correlated with the non-Saccharomyces yeast Hanseniaspora uvarum, as well as initial nitrogen concentrations in grape musts. These results highlight novel relationships between site-specific variables and Saccharomyces cerevisiae gene expression that are linked to repeated fermentation outcomes. It was also demonstrated that DMap-DE can extract biologically relevant gene expression patterns from other contexts (e.g., hypoxic response of Saccharomyces cerevisiae) and offers advantages over other data dimensionality reduction approaches, indicating that DMap-DE offers a robust method for investigating asynchronous time series gene expression data. IMPORTANCE In this work, Saccharomyces cerevisiae gene expression was used as a biosensor to capture differences across and between fermentations of Pinot noir grapes from 15 unique sites representing eight American Viticultural Areas. This required development of a novel analysis method, DMap-DE, for investigation of asynchronous gene expression data. It was demonstrated that DMap-DE reveals biologically relevant shifts in gene expression related to cell-environment interactions in the context of hypoxia and fermentation. Using these data, it was discovered that gene expression by non-Saccharomyces yeasts and initial nitrogen content in grape musts are correlated with differences in gene expression among fermentations. These findings highlight important relationships between site-specific variables and gene expression that may be used to understand why foods and beverages, including wine, possess sensory characteristics associated with or derived from their place of origin.

The Degenerate Tale of Ascidian Tails.

Ascidians are invertebrate chordates, with swimming chordate tadpole larvae that have distinct heads and tails. The head contains the small brain, sensory organs, including the ocellus (light) and otolith (gravity) and the presumptive endoderm, while the tail has a notochord surrounded by muscle cells and a dorsal nerve cord. One of the chordate features is a post-anal tail. Ascidian tadpoles are nonfeeding, and their tails are critical for larval locomotion. After hatching the larvae swim up toward light and are carried by the tide and ocean currents. When competent to settle, ascidian tadpole larvae swim down, away from light, to settle and metamorphose into a sessile adult. Tunicates are classified as chordates because of their chordate tadpole larvae; in contrast, the sessile adult has a U-shaped gut and very derived body plan, looking nothing like a chordate. There is one group of ascidians, the Molgulidae, where many species are known to have tailless larvae. The Swalla Lab has been studying the evolution of tailless ascidian larvae in this clade for over 30 years and has shown that tailless larvae have evolved independently several times in this clade. Comparison of the genomes of two closely related species, the tailed Molgula oculata and tailless Molgula occulta reveals much synteny, but there have been multiple insertions and deletions that have disrupted larval genes in the tailless species. Genomics and transcriptomics have previously shown that there are pseudogenes expressed in the tailless embryos, suggesting that the partial rescue of tailed features in their hybrid larvae is due to the expression of intact genes from the tailed parent. Yet surprisingly, we find that the notochord gene regulatory network is mostly intact in the tailless M. occulta, although the notochord does not converge and extend and remains as an aggregate of cells we call the "notoball." We expect that eventually many of the larval gene networks will become evolutionarily lost in tailless ascidians and the larval body plan abandoned, with eggs developing directly into an adult. Here we review the current evolutionary and developmental evidence on how the molgulids lost their tails.

Whole-genome assembly of Culex tarsalis.

The mosquito, Culex tarsalis, is a key vector in the western United States due to its role in transmission of zoonotic arboviruses that affect human health. Extensive research has been conducted on Cx. tarsalis ecology, feeding behavior, vector competence, autogeny, diapause, genetics, and insecticide resistance. Population genetic analyses in the western U.S. have identified at least three genetic clusters that are geographically distinct. However, in-depth genetic studies have been hindered by the lack of a reference genome. In this study, we present the first whole-genome assembly of this mosquito species (CtarK1) based on PacBio HiFi reads from high-molecular-weight DNA extracted from a single male. The CtarK1 assembly is 790 Mb with an N50 of 58 kb, which is 27% larger than Culex quinquefasciatus (578 Mb). This difference appears to be mostly composed of transposable elements. To annotate CtarK1, we used a previously assembled Cx. tarsalis transcriptome and approximately 17,456 protein genes from Cx. quinquefasciatus (N = 17,456). Genome completeness was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) tool, which identified 84.8% of the 2799 Dipteran BUSCO genes. Using a Bayesian phylogeny based on mitochondrial genomes, we place Cx. tarsalis in the context of other mosquito species and estimate the divergence between Cx. tarsalis and Cx. quinquefasciatus to be between 15.8 and 22.2 million years ago (MYA). Important next steps from this work include characterizing the genetic basis of diapause and sex determination in Culex mosquitoes.

MQF and buffered MQF: quotient filters for efficient storage of k-mers with their counts and metadata.

BACKGROUND: Specialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution. RESULT: Here, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~ tenfold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions. CONCLUSIONS: The MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data.