Biology subjects

Mitchell, K.

Publications and source records attributed to Mitchell, K..

At least 19 recordsLinked to original sources

bioRxiv2025

Characterization of quiescent subpopulations and proliferative compartments in glioblastoma

Glioblastoma (GBM) quiescent (Q) cell populations are hypothesized to contain cancer stem-like cells (CSC) that drive tumor growth, cellular heterogeneity, and recurrence. However, GBM tumors do not neatly resolve into developmental hierarchies and Q stem-like activities are difficult to assess. Here, we evaluated tumor Q subpopulations in patient-derived GBM xenograft tumors using live cell reporters, DNA label retention assays, and single cell genomics. Compared to adult neural stems cells (NSCs), GBM Q populations contain hybrid transcriptional states composed of networks found in both dormant and activated adult NSCs, resulting in constitutive expression of key Q egress transcription factors and their targets (e.g., AP-1 and CCND1/2). As a result, even the longest Q-residing cells ([~]12 days) in xenograft tumors continuously cycle and fail to enter dormant Q states. We provide evidence and hypothesize that transient Q states in primary tumors arise as part of distinct proliferative compartments rather than deterministic developmental hierarchies driven by CSC activity. We further speculate that increases in basal translation rates drive Q instability in GBM tumors.

cancer biology↗

bioRxiv2025

The RNA splicing factor PRPF8 is required for left-right organiser cilia function and determination of cardiac left-right asymmetry via regulation of Arl13b splicing

Cilia function in the left-right organizer (LRO) is critical for determining internal organ asymmetry in vertebrates. To further understand the genetics of left-right asymmetry, we isolated a mouse mutant with laterality defects, l11Jus27, from a random mutagenesis screen. l11Jus27 mutants carry a missense mutation in the pre-mRNA processing factor, Prpf8. cephaloph[o]nus (cph) mutant zebrafish, carrying a protein truncating mutation in prpf8, phenocopy the laterality defects of l11Jus27 mutants. Prpf8 mutant mouse and fish embryos have increased expression of an alternative transcript encoding the cilium-associated protein, ARL13B, that lacks exon 9. In zebrafish, over-expression of the arl13b transcript lacking exon 9 perturbed cilium formation and caused laterality defects. The shorter ARL13B protein isoform lacked interactions with intraflagellar transport proteins. Our data suggest that PRPF8 plays a prominent role in LRO cilia by through the regulation of alternative splicing of ARL13B, thus uncovering a new mechanism for cilia-linked developmental defects.

developmental biology↗

bioRxiv2024

Hormonal dynamics reveal a stimulatory role for secretoneurin in zebrafish ovulation

Surge release of luteinizing hormone (Lh) from the pituitary is essential for fertility as it triggers ovulation. While secretoneurin (SN) is a phylogenetically conserved secretogranin-2 derived peptide that stimulates Lh, its role in ovulation has not been established. To directly compare periovulatory changes in the classical hormones to the emerging reproductive neuropeptides SNa and SNb, simultaneous mass spectrometry measurement of 9 peptides and 5 steroids was conducted in female zebrafish. Regression analysis indicated that levels of SNa1-34 in the brain peaked when type 3 gonadotropin-releasing hormone (Gnrh3) increased (R2=0.71) at the time of the Lh surge, 3.5 h before ovulation. In contrast, levels of the naturally occurring derivative SNa1-14 were highest at ovulation, while SNb1-31 was invariable. The bioactivities of SNa1-34 and SNa1-14 were investigated. After injection of SNa1-34 in females that had been isolated from males, 61% (11/18) ovulated within 6 h, which was like the effects of the Lh analog human chorionic gonadotropin (hCG) (72%; 13/18 females). SNa1-34 could induce ovulation by stimulating time-dependent expression of gnrh3 in the brain, chorionic gonadotropin alpha (cga), luteinizing hormone b (lhb) subunit in pituitary, and the nuclear progesterone receptor (npr) in ovaries. In contrast, SNa1-14 exhibited far fewer effects on gene expression and did not induce ovulation. Our results support the proposal that SN is a reproductive hormone. Significance statementSecretogranin-2 is a secretory granule protein that is enzymatically processed to the bioactive neuropeptide secretoneurin. It is produced in hypothalamic neurons and anterior pituitary cells, and we provide in vivo evidence that secretoneurin plays an important role to induce ovulation. Secretoneurin levels in the brain increase concomitantly with gonadotropin-releasing hormone prior to ovulation in normal zebrafish. Injection of a synthetic secretoneurin peptide increased expression of reproduction-related genes at all levels of the hypothalamic-pituitary-ovarian axis. Secretoneurin stimulates ovulation in otherwise anovulatory females. Together these data place the evolutionarily conserved secretoneurin amongst other critical neuroendocrine regulators. Secretoneurin or synthetic agonists could be used to improve breeding in fish species, or to potentially help with infertility treatments

physiology↗

bioRxiv2024

The JNK and Hippo pathways control epithelial integrity and prevent tumour initiation by regulating an overlapping transcriptome

Epithelial organs maintain their integrity and prevent tumour initiation by actively removing defective cells, such as those that have lost apicobasal polarity. Here, we identify how transcription factors of two key signalling pathways - Jun-N-terminal kinase (JNK) and Hippo - regulate epithelial integrity by controlling transcription of an overlapping set of target genes. Targeted DamID experiments reveal that in proliferating cells of the Drosophila melanogaster eye, the AP-1 transcription factor Jun, and the Hippo pathway transcription regulators Yorkie and Scalloped bind to a common suite of target genes that regulate organ growth. In defective neoplastic cells, AP-1 transcription factors repress transcription of growth genes together with the CtBP co-repressor. If gene repression by AP-1/CtBP fails, neoplastic tumour growth ensues, driven by Yorkie/Scalloped. Thus, AP-1/CtBP eliminates defective cells and prevents tumour initiation by acting in parallel to Yorkie/Scalloped to repress expression of a shared transcriptome. These findings shed new light on the maintenance of epithelial integrity and tumour suppression.

developmental biology↗

bioRxiv2023

Skimming genomes for systematics and DNA barcodes of corals

1: Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage whole genome sequencing) remains a low-cost, promising method to not only extract high-copy loci, but also 100s to 1000s of phylogenetically informative single-copy nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and historical museum samples. The subphylum Anthozoa, which includes important ecosystem engineers (e.g., stony corals, black corals, anemones and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. 2: Genome skimming was conducted on 242 hexacorals and octocorals collected from 1890 to 2022. Using previously developed target-capture baitsets, we bioinformatically obtained UCEs and exons from the genome-skimming data and incorporated them with data from previously published target-capture studies. We also extracted partial to whole mitogenomes and nuclear rRNA genes from the skim data. 3: The mean number of UCE and exon loci extracted from the genome skimming data was 1,837 {+/-} 662 SD for octocorals and 1,422 {+/-} 720 loci for hexacorals; phylogenetic relationships were well resolved within each class. A mean of 1,422 {+/-} 720 loci were obtained from the historical museum specimens, with 1,253 loci recovered from the oldest specimen collected in 1886 and 1,336 loci recovered from a holotype. The nuclear rRNA genes and the majority of mitochondrial genes were successfully obtained from >95% of samples. Out of 99 circularized mitogenomes, 88% were recovered in samples from which we obtained >15M paired-end (PE) reads (>30M total reads); there was more variability in whether mitogenomes were circularized or not in samples with <15M PE reads. 4: Bioinformatically pulling UCEs, exons, mitochondrial genomes, and nuclear rRNA genes from genome skimming is a viable and low-cost option for phylogenetic studies. This approach can be used to review and support taxonomic revisions and reconstruct evolutionary histories, including historical museum and type specimens.

evolutionary biology↗

bioRxiv2023

Ancient mitogenomes reveal evidence for the late Miocene dispersal of mergansers to the Southern Hemisphere

Mergansers are riverine and coastal piscivorous ducks that are widespread throughout North America and Eurasia but uncommon in the Southern Hemisphere. One species occurs in South America and at least two extinct species from New Zealand. It has been proposed that Southern Hemisphere mergansers were founded by independent dispersal events from the Northern Hemisphere. However, some morphological and behavioural evidence suggests that Southern Hemisphere mergansers may be closely related to one another. They share several characteristics that differ from Northern Hemisphere mergansers (e.g., non-migratory vs. migratory, sexual monochromatism vs. sexual dichromatism, long vs. short pair bonds). We sequenced complete mitogenomes from the Brazilian merganser and an extinct merganser from New Zealand--the Auckland Island merganser. Our results show the Brazilian and Auckland Island mergansers form a monophyletic clade with the common merganser, and that a sister relationship between Southern Hemisphere mergansers cannot be rejected. We cannot exclude the possibility that the Brazilian and Auckland Island mergansers descend from a single dispersal event from the Northern Hemisphere at least seven million years ago. Nuclear (palaeo)genomic data may help to resolve the relationship between living and extinct mergansers, including merganser fossils from New Zealand that have not been subjected to palaeogenetic analysis.

genetics↗

bioRxiv2023

Functional genomic analysis of adult and pediatric brain tumor isolates

BackgroundAdult and pediatric tumors display stark differences in their mutation spectra and chromosome alterations. Here, we attempted to identify common and unique gene dependencies and their associated biomarkers among adult and pediatric tumor isolates using functional genetic lethal screens and computational modeling. MethodsWe performed CRISRP-Cas9 lethality screens in two adult glioblastoma (GBM) tumor isolates and five pediatric brain tumor isolates representing atypical teratoid rhabdoid tumors (ATRT), diffuse intrinsic pontine glioma, GBM, and medulloblastoma. We then integrated the screen results with machine learning-based gene-dependency models generated from data from >900 cancer cell lines. ResultsWe found that >50% of candidate dependencies of 280 identified were shared between adult GBM tumors and individual pediatric tumor isolates. 68% of screen hits were found as nodes in our network models, along with shared and tumor-specific predictors of gene dependencies. We investigated network predictors associated with ADAR, EFR3A, FGFR1 (pediatric-specific), and SMARCC2 (ATRT-specific) gene dependency among our tumor isolates. ConclusionsThe results suggest that, despite harboring disparate genomic signatures, adult and pediatric tumor isolates share a preponderance of genetic dependences. Further, combining data from primary brain tumor lethality screens with large cancer cell line datasets produced valuable insights into biomarkers of gene dependency, even for rare cancers. Importance of the StudyOur results demonstrate that large cancer cell lines data sets can be computationally mined to identify known and novel gene dependency relationships in adult and pediatric human brain tumor isolates. Gene dependency networks and lethality screen results represent a key resource for neuro-oncology and cancer research communities. We also highlight some of the challenges and limitations of this approach.

cancer biology↗

bioRxiv2022

kimma: flexible linear mixed effects modeling with kinship for RNA-seq data

We introduce kimma (Kinship In Mixed Model Analysis), an open-source R package for flexible linear mixed effects modeling of RNA-seq including covariates, weights, random effects, covariance matrices, and fit metrics. In simulated datasets, kimma detects differentially expressed genes (DEGs) with similar specificity, sensitivity, and computational time as limma unpaired and dream paired models. Unlike other software, kimma supports covariance matrices as well as fit metrics like AIC. Utilizing genetic kinship covariance, kimma revealed that kinship impacts model fit and DEG detection in a related cohort. Thus, kimma equals or outcompetes current DEG pipelines in sensitivity, computational time, and model complexity.

bioinformatics↗

bioRxiv2022

KAT5 activity regulates G0-like states in human gliomas

In solid tumors, G0-like states are likely critical for maintaining developmental hierarchies and cellular heterogeneity and promoting tumor growth/recurrence, yet little is known about tumor G0 states or regulation of their ingress/egress. To discover G0-like states and their regulators for glioblastoma (GBM), we analyzed G0 populations in an orthotopic model of GBM using single cell RNA-seq and performed a genome-wide CRISPR-Cas9 screen in patient-derived GBM stem-like cells (GSCs) for genes that trap cells in G0 when inhibited. We identify the protein acetyltransferase KAT5 as a key regulator of transcriptional, epigenetic, and proliferative heterogeneity impacting transitions into G0-like states. KAT5 activity suppresses the emergence of non-dividing subpopulations with oligodendrocyte progenitor and radial glial cell characteristics both in vitro and in a human GSC brain tumor model. In primary gliomas, KAT5 activity is dynamic with KAT5low tumor cells displaying quiescent properties, while KAT5 activity overall increases from low to high grade tumors and is associated with worse patient outcomes.

cancer biology↗

bioRxiv2022

VRK1 is a Paralog Synthetic Lethal Target in VRK2-methylated Glioblastoma

Synthetic lethality -- a genetic interaction that results in cell death when two genetic deficiencies co-occur but not when either deficiency occurs alone -- can be co-opted for cancer therapeutics. A pair of paralog genes is among the most straightforward synthetic lethal interaction by virtue of their redundant functions. Here we demonstrate a paralog-based synthetic lethality by targeting Vaccinia-Related Kinase 1 (VRK1) in Vaccinia-Related Kinase 2 (VRK2)-methylated glioblastoma (GBM). VRK2 is silenced by promoter methylation in approximately two-thirds of GBM, an aggressive cancer with few available targeted therapies. Genetic knockdown of VRK1 in VRK2-null or VRK2-methylated cells results in decreased activity of the downstream substrate Barrier to Autointegration Factor (BAF), a regulator of post-mitotic nuclear envelope formation. VRK1 knockdown, and thus reduced BAF activity, causes nuclear lobulation, blebbing and micronucleation, which subsequently results in G2/M arrest and DNA damage. The VRK1-VRK2 synthetic lethal interaction is dependent on VRK1 kinase activity and is rescued by ectopic VRK2 expression. Knockdown of VRK1 leads to robust tumor growth inhibition in VRK2-methylated GBM xenografts. These results indicate that inhibiting VRK1 kinase activity could be a viable therapeutic strategy in VRK2-methylated GBM.

cancer biology↗

bioRxiv2021

SerpinB3 drives cancer stem cell survival in glioblastoma

Despite therapeutic interventions for glioblastoma (GBM), cancer stem cells (CSCs) drive recurrence. The precise mechanisms underlying CSC therapeutic resistance, namely inhibition of cell death, are unclear. We built on previous observations that the high cell surface expression of junctional adhesion molecule-A drives CSC maintenance and identified downstream signaling networks, including the cysteine protease inhibitor SerpinB3. Using genetic depletion approaches, we found that SerpinB3 is necessary for CSC maintenance, survival, and tumor growth, as well as CSC pathway activation. The knockdown of SerpinB3 also increased apoptosis and susceptibility to radiation therapy. Mechanistically, SerpinB3 was essential to buffer cathepsin L-mediated cell death, which was enhanced with radiation. Finally, we found that SerpinB3 knockdown dramatically increased the efficacy of radiation in pre-clinical models. Taken together, our findings identify a novel GBM CSC-specific survival mechanism involving a previously uninvestigated cysteine protease inhibitor, SerpinB3, and provide a potential target to improve the efficacy of standard-of-care GBM therapies against therapeutically resistant CSCs. SummaryLauko et al. demonstrate a functional role for SerpinB3, which is elevated in glioblastoma cancer stem cells and protects against lysosomal-mediated cell death. SerpinB3 can be targeted to increase the efficacy of radiation in glioblastoma pre-clinical models.

cancer biology↗

bioRxiv2021

The WRAD complex represents a therapeutically exploitable target for cancer stem cells in glioblastoma

Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors that are driven by populations of cancer stem cells (CSCs). Despite their importance for tumor growth, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy resistant niche and identified WDR5 as indispensable for this population. WDR5 is a component of the WRAD complex, which promotes SET1-family-mediated Lys4 methylation of histone H3, associated with positive regulation of transcription. In GBM CSC models, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, including the POU5F1(OCT4)::SOX2 motif. We incorporated a SOX2/OCT4 motif driven GFP reporter system into our CSC cell models and found that WDR5 inhibitor treatment diminished reporter activity. Further, WDR5 inhibitor treatment altered the stem cell state, disrupting CSC in vitro growth and self-renewal as well as in vivo tumor growth. These findings highlight the role of WDR5 and the WRAD complex in maintaining the CSC state and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers. SignificanceIn this study, we perform an epigenetic-focused functional genomics screen in glioblastoma organoids and identify WDR5 as an essential epigenetic regulator in the SOX2-enriched, therapy resistant cancer stem cell niche. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=135 HEIGHT=200 SRC="FIGDIR/small/461125v2_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@bc5c5eorg.highwire.dtl.DTLVardef@545a2borg.highwire.dtl.DTLVardef@1ebd3c9org.highwire.dtl.DTLVardef@19d5d30_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

An age-depth model and revised stratigraphy of vertebrate-bearing units in Natural Trap Cave, Wyoming

Almost a half-century ago excavations at Natural Trap Cave (NTC) began to yield evidence of the steppe paleoecology along the western slope of the Bighorn Mountains in north central Wyoming. The first decade of fieldwork led to the discovery of a diverse fauna that existed at the end of the Last Glacial Maximum. Stratigraphic deposits below the entrance of the cave were studied soon after excavations began, but never formally published. Although stratigraphy, taphonomy, and depositional circumstances were briefly discussed over the following years, little has been done to correlate the numerous stratigraphic schemes used by various authors. In this study, four stratigraphic sections were measured and analysed to establish an easily modifiable lithostratigraphic system of nomenclature. We provide the first correlations of all stratigraphic nomenclature used throughout excavations at NTC to facilitate comparisons with current and previous collections and publications. By leveraging more than 100 radioisotopic dates we developed an age-depth model and chronostratigraphic framework to further interrogate spatiotemporal relationships between strata, paleoenvironmental proxies, and fossil assemblages. Deposition is shown to be discontinuous; sediment accumulation in the study area is restricted to the buildup through peak penultimate and Last Glacial maxima. More recent (<10 ka) Holocene deposits unconformably cover the eroded surface of underlying Pleistocene strata. There is active reworking of sediments with transport and deposition of reactivated sediments within the Lower Chamber. We note that the two hiatuses coincide with interglacial periods and may reflect changing depositional circumstances within the cave such as extended periods of non-deposition, erosion, or bypass (possibly leading to deposition in the Lower Chamber). Contrary to previous reports, we demonstrate that it is unlikely a prominent snow cone existed or contributed to the pattern of sediment and fossil distribution within the study area, furthermore, we do not observe a continuous Pleistocene-Holocene transition in the study area. Further stratigraphic work will be needed to better understand the interrelationship between Main and Lower chamber deposits and the evolution of sediment accumulation in NTC.

paleontology↗

bioRxiv2021

Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samples

Estimating cell type composition of blood and tissue samples is a biological challenge relevant in both laboratory studies and clinical care. In recent years, a number of computational tools have been developed to estimate cell type abundance using gene expression data. While these tools use a variety of approaches, they all leverage expression profiles from purified cell types to evaluate the cell type composition within samples. In this study, we compare ten deconvolution tools and evaluate their performance while using each of eleven separate reference profiles. Specifically, we have run deconvolution tools on over 4,000 samples with known cell type proportions, spanning both immune and stromal cell types. Twelve of these represent in vitro synthetic mixtures and 300 represent in silico synthetic mixtures prepared using single cell data. A final 3,728 clinical samples have been collected from the Framingham Cohort, for which cell populations have been quantified using electrical impedance cell counting. When tools are applied to the Framingham dataset, the tool EPIC produces the highest correlation while GEDIT produces the lowest error. The best tool for other datasets is varied, but CIBERSORT and GEDIT most consistently produce accurate results. In terms of reference choice, we find that the Human Primary Cell Atlas (HPCA) and references published by the EPIC authors produce accurate results for the largest number of tools and datasets. When applying deconvolution to blood samples, the leukocyte reference matrix LM22 is also a suitable choice, usually (but not always) outperforming HPCA and EPIC. Running time varies substantially across tools. For as many as 5052 samples, SaVanT and dtangle reliably finish in under one minute, while slower tools may require up to two hours. However, when using custom references, CIBERSORT can run very slowly, taking over 24 hours to complete for large datasets. We conclude that combining the best tools with optimal reference datasets can provide significant gains in accuracy when carrying out deconvolution tasks.

bioinformatics↗

bioRxiv2020

TAZ-CAMTA1 and YAP-TFE3 modulate the basal TAZ/YAP transcriptional program by recruiting the ATAC histone acetyltransferase complex

Epithelioid hemangioendothelioma (EHE) is a vascular sarcoma that metastasizes early and lacks an effective medical therapy. The TAZ-CAMTA1 and YAP-TFE3 fusion proteins are chimeric transcription factors and initiating oncogenic drivers of EHE. A combined proteomic/genetic screen identified YEATS2 and ZZZ3, components of the Ada2a-containing histone acetyltransferase (ATAC) complex, as key interactors of both TAZ-CAMTA1 and YAP-TFE3 despite the dissimilarity of the C terminal fusion partners CAMTA1 and TFE3. An integrative next generation sequencing approach showed the fusion proteins drive expression of a unique transcriptome distinct from TAZ and YAP by simultaneously hyperactivating a TEAD-based transcriptional program and modulating the chromatin environment via interaction with the ATAC complex. Interaction of the ATAC complex with both TAZ-CAMTA1 and YAP-TFE3 indicates the histone acetyltransferase complex is an oncogenic driver in EHE and potentially other sarcomas. Furthermore, the ATAC complex is an enzymatic transcriptional cofactor required for both fusion proteins in EHE, representing a unifying therapeutic target for this sarcoma. Gene fusions are the most common genetic alterations activating TAZ and YAP in cancer, and this study serves as a template for identifying epigenetic modifiers recruited by the C terminal fusion partners of other TAZ/YAP gene fusions occurring in gliomas, carcinomas, and other sarcomas. SummaryTAZ-CAMTA1 and YAP-TFE3 alter the TAZ/YAP transcriptional program by recruiting the ATAC complex and modifying the chromatin landscape.

cancer biology↗

bioRxiv2019

Benchmarking of computational error-correction methods for next-generation sequencing via unique molecular identifiers

BackgroundRecent advancements in next-generation sequencing have rapidly improved our ability to study genomic material at an unprecedented scale. Despite substantial improvements in sequencing technologies, errors present in the data still risk confounding downstream analysis and limiting the applicability of sequencing technologies in clinical tools. Computational error-correction promises to eliminate sequencing errors, but the relative accuracy of error correction algorithms remains unknown. ResultsIn this paper, we evaluate the ability of error-correction algorithms to fix errors across different types of datasets that contain various levels of heterogeneity. We highlight the advantages and limitations of computational error correction techniques across different domains of biology, including immunogenomics and virology. To demonstrate the efficacy of our technique, we apply the UMI-based high-fidelity sequencing protocol to eliminate sequencing errors from both simulated data and the raw reads. We then perform a realistic evaluation of error correction methods. ConclusionsIn terms of accuracy, we find that method performance varies substantially across different types of datasets with no single method performing best on all types of examined data. Finally, we also identify the techniques that offer a good balance between precision and sensitivity

bioinformatics↗

bioRxiv2018

PUMA: A tool for processing 16S rRNA taxonomy data for analysis and visualization

Microbial community profiling and functional inference via 16S rRNA analysis is quickly expanding across various areas of microbiology due to improvements to technology. There are numerous platforms for producing 16S rRNA taxonomic data which often vary in file and sequence formatting, creating a common barrier in microbiome studies. Additionally, many of the methods for analyzing and visualizing this sequencing data each require their own specific formatting. As a result, efficient and reproducible comparative analysis of taxonomic data and corresponding metadata in multiple programs remains a challenge in the investigation of microbial communities. PUMA, the Program for Unifying Microbiome Analysis, alleviates this problem in microbiome studies by allowing users to take advantage of numerous 16S rRNA taxonomic identification platforms and analysis tools in an efficient manner. PUMA accepts sequencing results from several taxonomic identification platforms and then automates configuration of data and file types for analysis and visualization via many popular tools. The protocol accomplishes this by producing a variety of properly configured, annotated, and altered files for both analysis and visualization of taxonomic community profiles and inferred functional profiles. PUMA provides an easy and flexible interface to accommodate for a variety of users to produce all files needed for all-inclusive analysis of targeted amplicon sequencing studies. PUMA is an unprecedented open-source solution for unifying multiple microbiome analysis softwares and uses an adaptable implementation with the potential to improve and consolidate the state of microbiome research.\n\nBody/Findings

microbiology↗

bioRxiv2018

A comprehensive analysis of the usability and archival stability of omics computational tools and resources

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through URLs published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed \"easy to install,\" and 28% of the tools failed to be installed at all due to problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.

bioinformatics↗