The Spread of SARS-CoV-2 Omicron Variant in CALABRIA: A Spatio-Temporal Report of Viral Genome Evolution

Seroprevalence and age-related susceptibility of TORCH infections in childbearing age women: A 5-year cross-sectional retrospective study and a literature review

BACKGROUND

Serodiagnosis of TORCH infections should be performed in pre-pregnancy and reproductive-age women to prevent vertical transmission. Herein, we conducted a 5-year cross-sectional retrospective study in childbearing age women to provide prevalence data. Also, stratifying the cohort into three age groups, we identified those most susceptible to acute TORCH infections.

METHODS

Between 2019 and 2023, serum samples from 2286 childbearing age women attending the "R. Dulbecco" University Hospital of Catanzaro were collected. Screening for TORCH pathogens, such as: Toxoplasma gondii (TOX), Cytomegalovirus (CMV), Rubella Virus (RUB), Parvovirus B19 (ParvoB19), Herpes Simplex Virus types 1 and 2 (HSV1, HSV2) and Treponema pallidum was carried out using serological tests. Chemiluminescent immunoassay was performed to detect TOX, CMV and ParvoB19 Immunoglobulin M (IgM) and Immunoglobulin G (IgG) antibodies, while Enzyme Linked Fluorescent Assay was performed to detect RUB IgM and IgG antibodies and CMV and TOX IgG Avidity. Enzyme Linked Immunosorbent Assay was performed to detect HSV1 IgG, HSV2 IgG, HSV1/2 IgM, T. pallidum total antibodies and RUB IgG Avidity. Binomial logistic regression models were developed to compare seroprevalence rates among different age groups.

RESULTS

The highest immunological protection was observed for RUB infection (87 %), probably associated with vaccination practice, followed by HSV1 and CMV (82 % and 63 %). The 16-25 year age group results as the most susceptible to acute infections as demonstrated by odds of CMV IgM positivity (primary infection) which decreased with age.

CONCLUSIONS

The TORCH serological screening program should be implemented in women before pregnancy to formulate strategies for serological screening of childbearing age women and guiding clinicians in making decisions.

Prevalence of Enteric Pathogens and Antibiotic Resistance: Results of a Six-Year Active Surveillance Study on Patients Admitted to a Teaching Hospital

BACKGROUND

Acute Infectious Diarrhea (AID) and the short- and long-term complications associated with it are major causes of hospitalization worldwide. In Italy, due to a lack of robust surveillance programs, only limited data has been collected on their prevalence and circulation. This study aims to evaluate the resistance pattern of enteric pathogens and their epidemiological trends over a six-year period.

METHODS

This cross-sectional retrospective study was conducted from January 2018 to December 2023. Stool samples were analyzed during routine diagnosis with culture methods, syndromic molecular tests, and enzyme immunoassay.

RESULTS

Bacteria were the most isolated enteric pathogens (62.2%), followed by fungi (29.0%), viruses (8.2%), and parasites (0.6%). Most bacteria were isolated from outpatients (29.5%) and from patients in the Oncology ward (26.2%). The most prevalent target was EPEC (11.1%), followed by C. difficile toxin A/B-producing strains (8.3%), C. jejuni (2.5%), and S. enterica, (1%.). Norovirus and Candida spp. were the most prevalent in pediatric patients (6.5% and 39.6%, respectively). In the last years, enteric pathogens have been a frequent cause of infections characterized by a problematic resistance to common antimicrobials. In our study, S. enterica showed resistance to amikacin, gentamicin, ampicillin, levofloxacin, and ciprofloxacin. C. jejuni was susceptible to all tested drugs.

CONCLUSION

Timely notification of gastroenteric infections is crucial in identifying potential outbreak sources and ensuring strict adherence to food safety and hygiene practices, so as to protect the most vulnerable populations. The present study offers insights into the epidemiological characteristics and the antibiotic susceptibility of the main enteric AID pathogens in order to implement infection control measures in health care settings.

Persistence of SARS-CoV-2 infection and viral intra- and inter-host evolution in COVID-19 hospitalized patients

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) persistence in COVID-19 patients could play a key role in the emergence of variants of concern. The rapid intra-host evolution of SARS-CoV-2 may result in an increased transmissibility, immune and therapeutic escape which could be a direct consequence of COVID-19 epidemic currents. In this context, a longitudinal retrospective study on eight consecutive COVID-19 patients with persistent SARS-CoV-2 infection, from January 2022 to March 2023, was conducted. To characterize the intra- and inter-host viral evolution, whole genome sequencing and phylogenetic analysis were performed on nasopharyngeal samples collected at different time points. Phylogenetic reconstruction revealed an accelerated SARS-CoV-2 intra-host evolution and emergence of antigenically divergent variants. The Bayesian inference and principal coordinate analysis analysis showed a host-based genomic structuring among antigenically divergent variants, that might reflect the positive effect of containment practices, within the critical hospital area. All longitudinal antigenically divergent isolates shared a wide range of amino acidic (aa) changes, particularly in the Spike (S) glycoprotein, that increased viral transmissibility (K417N, S477N, N501Y and Q498R), enhanced infectivity (R346T, S373P, R408S, T478K, Q498R, Y505H, D614G, H655Y, N679K and P681H), caused host immune escape (S371L, S375F, T376A, K417N, and K444T/R) and displayed partial or complete resistance to treatments (G339D, R346K/T, S371F/L, S375F, T376A, D405N, N440K, G446S, N460K, E484A, F486V, Q493R, G496S and Q498R). These results suggest that multiple novel variants which emerge in the patient during persistent infection, might spread to another individual and continue to evolve. A pro-active genomic surveillance of persistent SARS-CoV-2 infected patients is recommended to identify genetically divergent lineages before their diffusion.

Evolution of in-hospital patient characteristics and predictors of death in the COVID-19 pandemic across four waves: are they moving targets with implications for patient care?

Objectives

The aim of this work was to study characteristics, outcomes and predictors of all-cause death in inpatients with SARS-CoV-2 infection across the pandemic waves in one large teaching hospital in Italy to optimize disease management.

Methods

All patients with SARS-CoV-2 infection admitted to our center from March 2020 to June 2022 were included in this retrospective observational cohort study. Both descriptive and regression tree analyses were applied to identify factors influencing all-cause mortality.

Results

527 patients were included in the study (65.3% with moderate and 34.7% with severe COVID-19). Significant evolutions of patient characteristics were found, and mortality increased in the last wave with respect to the third wave notwithstanding vaccination. Regression tree analysis showed that in-patients with severe COVID-19 had the greatest mortality across all waves, especially the older adults, while prognosis depended on the pandemic waves in patients with moderate COVID-19: during the first wave, dyspnea was the main predictor, while chronic kidney disease emerged as determinant factor afterwards.

Conclusion

Patients with severe COVID-19, especially the older adults during all waves, as well as those with moderate COVID-19 and concomitant chronic kidney disease during the most recent waves require more attention for monitoring and care. Therefore, our study drives attention towards the importance of co-morbidities and their clinical impact in patients with COVID-19 admitted to hospital, indicating that the healthcare system should adapt to the evolving features of the epidemic.

The spike-specific TCRβ repertoire shows distinct features in unvaccinated or vaccinated patients with SARS-CoV-2 infection

BACKGROUND

The evolving variants of SARS-CoV-2 may escape immunity from prior infections or vaccinations. It's vital to understand how immunity adapts to these changes. Both infection and mRNA vaccination induce T cells that target the Spike protein. These T cells can recognize multiple variants, such as Delta and Omicron, even if neutralizing antibodies are weakened. However, the degree of recognition can vary among people, affecting vaccine efficacy. Previous studies demonstrated the capability of T-cell receptor (TCR) repertoire analysis to identify conserved and immunodominant peptides with cross-reactive potential among variant of concerns. However, there is a need to extend the analysis of the TCR repertoire to different clinical scenarios. The aim of this study was to examine the Spike-specific TCR repertoire profiles in natural infections and those with combined natural and vaccine immunity.

METHODS

A T-cell enrichment approach and bioinformatic tools were used to investigate the Spike-specific TCRβ repertoire in peripheral blood mononuclear cells of previously vaccinated (n = 8) or unvaccinated (n = 6) COVID-19 patients.

RESULTS

Diversity and clonality of the TCRβ repertoire showed no significant differences between vaccinated and unvaccinated groups. When comparing the TCRβ data to public databases, 692 unique TCRβ sequences linked to S epitopes were found in the vaccinated group and 670 in the unvaccinated group. TCRβ clonotypes related to spike regions S135-177, S264-276, S319-350, and S448-472 appear notably more prevalent in the vaccinated group. In contrast, the S673-699 epitope, believed to have super antigenic properties, is observed more frequently in the unvaccinated group. In-silico analyses suggest that mutations in epitopes, relative to the main SARS-CoV-2 variants of concern, don't hinder their cross-reactive recognition by associated TCRβ clonotypes.

CONCLUSIONS

Our findings reveal distinct TCRβ signatures in vaccinated and unvaccinated individuals with COVID-19. These differences might be associated with disease severity and could influence clinical outcomes.

TRIAL REGISTRATION

FESR/FSE 2014-2020 DDRC n. 585, Action 10.5.12, noCOVID19@UMG.

The increase in SARS-CoV-2 lineages during 2020-2022 in a state in the Brazilian Northeast is associated with a number of cases

SARS-CoV-2 has caused a high number of deaths in several countries. In Brazil, there were 37 million confirmed cases of COVID-19 and 700,000 deaths caused by the disease. The population size and heterogeneity of the Brazilian population should be considered in epidemiological surveillance due to the varied tropism of the virus. As such, municipalities and states must be factored in for their unique specificities, such as socioeconomic conditions and population distribution. Here, we investigate the spatiotemporal dispersion of emerging SARS-CoV-2 lineages and their dynamics in each microregion from Sergipe state, northeastern Brazil, in the first 3 years of the pandemic. We analyzed 586 genomes sequenced between March 2020 and November 2022 extracted from the GISAID database. Phylogenetic analyses were carried out for each data set to reconstruct evolutionary history. Finally, the existence of a correlation between the number of lineages and infection cases by SARS-CoV-2 was evaluated. Aracaju, the largest city in northeastern Brazil, had the highest number of samples sequenced. This represented 54.6% (320) of the genomes, and consequently, the largest number of lineages identified. Studies also analyzed the relationship between mean lineage distributions and mean monthly infections, daily cases, daily deaths, and hospitalizations of vaccinated and unvaccinated patients. For this, a correlation matrix was created. Results revealed that the increase in the average number of SARS-CoV-2 variants was related to the average number of SARS-CoV-2 cases in both unvaccinated and vaccinated individuals. Thus, our data indicate that it is necessary to maintain epidemiological surveillance, especially in capital cities, since they have a high rate of circulation of resident and non-resident inhabitants, which contributes to the dynamics of the virus.

Characterization of SARS-CoV-2 Variants in Military and Civilian Personnel of an Air Force Airport during Three Pandemic Waves in Italy

We investigated SARS-CoV-2 variants circulating, from November 2020 to March 2022, among military and civilian personnel at an Air Force airport in Italy in order to classify viral isolates in a potential hotspot for virus spread. Positive samples were subjected to Next-Generation Sequencing (NGS) of the whole viral genome and Sanger sequencing of the spike coding region. Phylogenetic analysis classified viral isolates and traced their evolutionary relationships. Clusters were identified using 70% cut-off. Sequencing methods yielded comparable results in terms of variant classification. In 2020 and 2021, we identified several variants, including B.1.258 (4/67), B.1.177 (9/67), Alpha (B.1.1.7, 9/67), Gamma (P.1.1, 4/67), and Delta (4/67). In 2022, only Omicron and its sub-lineage variants were observed (37/67). SARS-CoV-2 isolates were screened to detect naturally occurring resistance in genomic regions, the target of new therapies, comparing them to the Wuhan Hu-1 reference strain. Interestingly, 2/30 non-Omicron isolates carried the G15S 3CLpro substitution responsible for reduced susceptibility to protease inhibitors. On the other hand, Omicron isolates carried unusual substitutions A1803V, D1809N, and A949T on PLpro, and the D216N on 3CLpro. Finally, the P323L substitution on RdRp coding regions was not associated with the mutational pattern related to polymerase inhibitor resistance. This study highlights the importance of continuous genomic surveillance to monitor SARS-CoV-2 evolution in the general population, as well as in restricted communities.

The Role of Gut Microbiota in the Clinical Outcome of Septic Patients: State of the Art and Future Perspectives

Sepsis is a life-threatening multiple-organ dysfunction caused by a dysregulated host response to infection, with high mortality worldwide; 11 million deaths per year are attributable to sepsis in high-income countries. Several research groups have reported that septic patients display a dysbiotic gut microbiota, often related to high mortality. Based on current knowledge, in this narrative review, we revised original articles, clinical trials, and pilot studies to evaluate the beneficial effect of gut microbiota manipulation in clinical practice, starting from an early diagnosis of sepsis and an in-depth analysis of gut microbiota.