Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion.

Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis

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

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

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

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

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%

Use of Maldi-Tof Mass spectrometry in direct microorganism identification in clinical laboratories

Mass Spectrometry is an old technique that has recently been introduced in the clinical microbiology laboratory as Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI is a soft ionization technique used in mass spectrometry that allows the analysis of biomolecules and large organic molecules which tend to be fragile and fragment when ionized.To obtain ions biological specimens are mixed with a matrix which specifically absorbs the ionization source (a laser beam). The high energy impact is followed by the formation of ions which are extract through an elastic field, focussed and detected as mass/charge (m/z) spectrum.The differences between ions are seen with TOF, a revelation system that relates the time of flight of a ion to the charge/mass value: ion with a higher m/z have are slower (a bigger time of flight) than ions with lower m/z. MALDI-TOF MS, in clinical microbiology laboratory, is used to identify bacteria and fungi directly from samples. The identification of microorganisms can be performed directly from body fluids (e.g. urine, blood culture, after centrifugation and recovery of microorganisms) or from colonies (after cultivation). The rapidity of identification is of great importance in blood cultures. Positive cultures with one microorganism are processed in a different way than those with more than one microorganism. In positive monomicrobial cultures, after separation of microbs from blood cells,we can perform an immediate identification with MALDI-TOF MS that we can communicate to the clinician, and that gives indication to perform the correct antibiogram. Major problems are present when more than one microorganism are in the culture: in this case we have to use the method of subcultivation and then the identification with mass-spectrometry can be performed. MALDI-TOF MS is a rapid, reliable and low cost technique, that can identify a growing number of microorganisms. This technique can significantly reduce the time to give an identification, that is of great importance, particularly in blood culture, where the success of therapy is strictly linked to its early beginning

Prevalence of Ureaplasma parvum in the area of Prato, Italy

In this study, the prevalence of Ureaplasma parvum in the area of Prato (Italy) was investigated. Samples from 1197 consecutive patients were analyzed. Our results showed that the prevalence of U. parvum was 33.6%, with a higher percentage in females than in males (40.6% vs 9%). In addition, the prevalence of U. parvum was significantly lower in older patients

MALDI-TOF mass spectrometry for the rapid identification of aetiological agents of sepsis

Introduction: The MALDI-TOF has recently become part of the methods of microbiological investigation in many laboratories of bacteriology with advantages both practical and economical.The use of this technique for the rapid identification of the causative agents of sepsis is of strategic importance to the ability to provide the clinician with useful information for a prompt and rapid establishment of an empirical antimicrobial “targeted” therapy. Methods: It was tested a total of 343 positive blood culture bottles from 211 patients. The samples after collection were incubated in the BACTEC FX (Becton Dickinson, USA). From these bottles were taken a few milliliters of broth culture and transferred into a vacutainer tube containing gel. This was centrifuged, the supernatant was decanted, and finally recovered the bacterial suspension on the gel. With micro-organisms recovered in this way, after several washes with distilled water, was prepared a slide for microscopic examination with Gram stain, and a plate for mass spectrometry (MS-Vitek, bioMérieux, France).Then, the same samples were inoculated on solid agar media according to the protocol in use in our laboratory.The next day was checked the possible bacterial growth on solid media; we then proceeded to the identification of the colonies by Vitek MS and / or with the system Vitek2 (bioMérieux, France). Results: 258 (75.2%) positive vials show concordant results between direct identification and identification after growth on agar. For 83 (24.2%) positive bottles there has been full compliance with the microscopic examination but not with culture. In particular, two bottles (0.6%) have given complete discordance between the direct identification and that after growth. Conclusions: The protocol we use for the direct identification of organisms responsible for sepsis, directly on positive bottles, seems to be a quick and inexpensive procedure, which in less than 60 minutes can give valuable feedback to the clinician