Enormous expansion of the chemosensory gene repertoire in the omnivorous German cockroach Blattella germanica.

The acquisition of genome sequences from a wide range of insects and other arthropods has revealed a broad positive correlation between the complexity of their chemical ecology and the size of their chemosensory gene repertoire. The German cockroach Blattella germanica is an extreme omnivore and has the largest chemosensory gene repertoire known for an arthropod, exceeding even the highly polyphagous spider mite Tetranychus urticae. While the Odorant Receptor family is not particularly large, with 123 genes potentially encoding 134 receptors (105 intact), the Gustatory Receptor family is greatly expanded to 431 genes potentially encoding 545 receptors (483 intact), the largest known for insects and second only to the spider mite. The Ionotropic Receptor family of olfactory and gustatory receptors is vastly expanded to at least 897 genes (604 intact), the largest size known in arthropods, far surpassing the 150 known from the dampwood termite Zootermopsis nevadensis. Commensurately, the Odorant Binding Protein family is expanded to the largest known for insects at 109 genes (all intact). Comparison with the far more specialized, but phylogenetically related termite, within the Dictyoptera, reveals considerable gene losses from the termite, and massive species-specific gene expansions in the cockroach. The cockroach has lost function of 11%-41% of these three chemoreceptor gene families to pseudogenization, and most of these are young events, implying rapid turnover of genes along with these major expansions, presumably in response to changes in its chemical ecology.

Development and validation of a deep learning-based microsatellite instability predictor from prostate cancer whole-slide images.

Microsatellite instability-high (MSI-H) is a tumor-agnostic biomarker for immune checkpoint inhibitor therapy. However, MSI status is not routinely tested in prostate cancer, in part due to low prevalence and assay cost. As such, prediction of MSI status from hematoxylin and eosin (H&E) stained whole-slide images (WSIs) could identify prostate cancer patients most likely to benefit from confirmatory testing to evaluate their eligibility for immunotherapy and need for Lynch syndrome testing. Prostate biopsies and surgical resections from prostate cancer patients referred to our institution were analyzed. MSI status was determined by next-generation sequencing. Patients sequenced before a cutoff date formed an algorithm development set (n = 4015, MSI-H 1.8%) and a paired validation set (n = 173, MSI-H 19.7%) that consisted of two serial sections from each sample, one stained and scanned internally and the other at an external site. Patients sequenced after the cutoff date formed a temporally independent validation set (n = 1350, MSI-H 2.3%). Attention-based multiple instance learning models were trained to predict MSI-H from H&E WSIs. The predictor achieved area under the receiver operating characteristic curve values of 0.78 (95% CI [0.69-0.86]), 0.72 (95% CI [0.63-0.81]), and 0.72 (95% CI [0.62-0.82]) on the internally prepared, externally prepared, and temporal validation sets, respectively, showing effective predictability and generalization to both external staining/scanning processes and temporally independent samples. While MSI-H status is significantly correlated with Gleason score, the model remained predictive within each Gleason score subgroup.

Precision health diagnostic and surveillance network uses S gene target failure (SGTF) combined with sequencing technologies to track emerging SARS-CoV-2 variants.

INTRODUCTION: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic revealed a worldwide lack of effective molecular surveillance networks at local, state, and national levels, which are essential to identify, monitor, and limit viral community spread. SARS-CoV-2 variants of concern (VOCs) such as Alpha and Omicron, which show increased transmissibility and immune evasion, rapidly became dominant VOCs worldwide. Our objective was to develop an evidenced-based genomic surveillance algorithm, combining reverse transcription polymerase chain reaction (RT-PCR) and sequencing technologies to quickly identify highly contagious VOCs, before cases accumulate exponentially. METHODS: Deidentified data were obtained from 508,969 patients tested for coronavirus disease 2019 (COVID-19) with the TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) in four CLIA-certified clinical laboratories in Puerto Rico (n = 86,639) and in three CLIA-certified clinical laboratories in the United States (n = 422,330). RESULTS: TaqPath data revealed a frequency of S Gene Target Failure (SGTF) > 47% for the last week of March 2021 in both, Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021. The weekly SGTF rate in US samples was high (>8%) from late December to early January and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico was concurrent with a sharp increase in VOCs among all SARS-CoV-2 sequences from Puerto Rico uploaded to Global Influenza Surveillance and Response System (GISAID) (n = 461). Alpha variant frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021. CONCLUSIONS: According to the proposed evidence-based algorithm, approximately 50% of all SGTF patients should be managed with VOCs self-quarantine and contact tracing protocols, while WGS confirms their lineage in genomic surveillance laboratories. Our results suggest this workflow is useful for tracking VOCs with SGTF.