A SAMPLING STRATEGY FOR RECENT AND FOSSIL BRACHIOPODS: SELECTING THE OPTIMAL SHELL SEGMENT FOR GEOCHEMICAL ANALYSES

Recent and fossil brachiopod shells have a long record as biomineral archives for (palaeo)climatic and (palaeo)environmental reconstructions, as they lack or exhibit limited vital effects in their calcite shell and generally are quite resistant to diagenetic alteration. Despite this, only few studies address the issue of identifying the best or optimal part of the shell for geochemical analyses. We investigated the link between ontogeny and geochemical signatures recorded in different parts of the shell. To reach this aim, we analysed the elemental (Ca, Mg, Sr, Na) and stable isotope (δ18O, δ13C) compositions of five recent brachiopod species (Magellania venosa, Liothyrella uva, Aerothyris kerguelensis, Liothyrella neozelanica and Gyphus vitreus), spanning broad geographical and environmental ranges (Chile, Antarctica, Indian Ocean, New Zealand and Italy) and having different shell layer successions (two-layer and three-layer shells). We observed similar patterns in the ventral and dorsal valves of these two groups, but different ontogenetic trends by the two- and three-layer shells in their trace element and stable isotope records. Our investigation led us to conclude that the optimal region to sample for geochemical and isotope analyses is the middle part of the mid-section of the shell, avoiding the primary layer, posterior and anterior parts as well as the outermost part of the secondary layer in recent brachiopods. Also, the outermost and innermost rims of shells should be avoided due to diagenetic impacts on fossil brachiopods

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Carriers of single pathogenic variants of the CFTR (cystic fibrosis transmembrane conductance regulator) gene have a higher risk of severe COVID-19 and 14-day death. The machine learning post-Mendelian model pinpointed CFTR as a bidirectional modulator of COVID-19 outcomes. Here, we demonstrate that the rare complex allele [G576V;R668C] is associated with a milder disease via a gain-of-function mechanism. Conversely, CFTR ultra-rare alleles with reduced function are associated with disease severity either alone (dominant disorder) or with another hypomorphic allele in the second chromosome (recessive disorder) with a global residual CFTR activity between 50 to 91%. Furthermore, we characterized novel CFTR complex alleles, including [A238V;F508del], [R74W;D1270N;V201M], [I1027T;F508del], [I506V;D1168G], and simple alleles, including R347C, F1052V, Y625N, I328V, K68E, A309D, A252T, G542*, V562I, R1066H, I506V, I807M, which lead to a reduced CFTR function and thus, to more severe COVID-19. In conclusion, CFTR genetic analysis is an important tool in identifying patients at risk of severe COVID-19

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Thrombosis of small and large vessels is reported as a key player in COVID-19 severity. However, host genetic determinants of this susceptibility are still unclear. Congenital Thrombotic Thrombocytopenic Purpura is a severe autosomal recessive disorder characterized by uncleaved ultra-large vWF and thrombotic microangiopathy, frequently triggered by infections. Carriers are reported to be asymptomatic. Exome analysis of about 3000 SARS-CoV-2 infected subjects of different severities, belonging to the GEN-COVID cohort, revealed the specific role of vWF cleaving enzyme ADAMTS13 (A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 13). We report here that ultra-rare variants in a heterozygous state lead to a rare form of COVID-19 characterized by hyper-inflammation signs, which segregates in families as an autosomal dominant disorder conditioned by SARS-CoV-2 infection, sex, and age. This has clinical relevance due to the availability of drugs such as Caplacizumab, which inhibits vWF-platelet interaction, and Crizanlizumab, which, by inhibiting P-selectin binding to its ligands, prevents leukocyte recruitment and platelet aggregation at the site of vascular damage

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as "Respiratory or thoracic disease", supporting their link with COVID-19 severity outcome.A multifaceted computational strategy identifies 16 genetic variants contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing dataset of a cohort of Italian patients

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an “end-on” manner. uSTA-guided modeling and a high-resolution cryo–electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%

Recent brachiopods from the South China Sea, NW Pacific

Three articulated brachiopod species have been recognized in material collected during the 2014 French-Taiwanese cruise DongSha to the South China Sea, NW Pacific: Terebratulina japonica (Sowerby, 1846), Macandrevia sp. and Nipponithyris afra Cooper, 1973. Nipponithyris afra is noted for the first time from the Northern Hemisphere and the genus Macandrevia is reported for the first time from the West Pacific. All species are reported for the first time from the South China Sea, extending their biogeographical range. </jats:p

Terebratulina d'Orbigny 1847

Genus &lt;i&gt;Terebratulina&lt;/i&gt; d&rsquo;Orbigny, 1847 &lt;p&gt; &lt;b&gt;Type species.&lt;/b&gt; &lt;i&gt;Anomia retusa&lt;/i&gt; Linnaeus, 1758.&lt;/p&gt;Published as part of &lt;i&gt;Bitner, Maria Aleksandra &amp; Romanin, Marco, 2017, Recent brachiopods from the South China Sea, NW Pacific, pp. 287-290 in Zootaxa 4306 (2)&lt;/i&gt; on page 287, DOI: 10.11646/zootaxa.4306.2.9, &lt;a href="http://zenodo.org/record/843838"&gt;http://zenodo.org/record/843838&lt;/a&gt

Nipponithyris Yabe & Hatai 1934

Genus &lt;i&gt;Nipponithyris&lt;/i&gt; Yabe &amp; Hatai, 1934 &lt;p&gt; &lt;b&gt;Type species.&lt;/b&gt; &lt;i&gt;Nipponithyris nipponensis&lt;/i&gt; Yabe &amp; Hatai, 1934.&lt;/p&gt;Published as part of &lt;i&gt;Bitner, Maria Aleksandra &amp; Romanin, Marco, 2017, Recent brachiopods from the South China Sea, NW Pacific, pp. 287-290 in Zootaxa 4306 (2)&lt;/i&gt; on page 289, DOI: 10.11646/zootaxa.4306.2.9, &lt;a href="http://zenodo.org/record/843838"&gt;http://zenodo.org/record/843838&lt;/a&gt