Development and characterization of fermented soy beverages containing encapsulated or non-encapsulated vaginal probiotics

Human microbial niches such as the healthy vagina, are recently emerging as “unconventional” sources of candidate probiotics capable of preventing from different vaginal diseases. These microorganisms could be provided as oral preparations since they can reach the vaginal niche passing through the gastrointestinal tract. However, their use in food would be challenging. The aim of this work was to develop and characterize fermented soy beverages with encapsulated and non-encapsulated vaginal lactobacilli, namely Lactobacillus crispatus BC4 and Lactobacillus gasseri BC9, as future dietary strategies for vaginal dysbiosis. The viability of vaginal strains remained stable at 7 log CFU/mL of product during the entire 28 days of storage, despite the use of encapsulated or non-encapsulated bacteria. Samples containing encapsulated bacteria, especially E-BC4+BC9, showed higher Water Holding Capacity (62.29%), lactic acid content (1.43%), and a remarkable antagonistic activity against enteropathogens. Moreover, encapsulation protected the strains from simulated GIT conditions (>1 Log) but reduced the acceptability of the final products. Overall, strain BC4 and BC9, alone or in mix, demonstrated to be promising co-starter cultures providing a characteristic flavor (pleasant smell and taste) and aroma (lower hexanal, benzaldehyde and higher diacetyl, and 2,3-pentanedione, compared to control) to the fermented soy beverages

Unravelling the Potential of Lactococcus lactis Strains to Be Used in Cheesemaking Production as Biocontrol Agents

This research, developed within an exchange program between Italy and Canada, represents the first step of a three-year project intended to evaluate the potential of nisin-producing Lactococcus lactis strains isolated from Italian and Canadian dairy products to select a consortium of strains to be used as biocontrol agents in Crescenza and Cheddar cheese production. In this framework, the acidification and the production of nisin in milk, and the volatile molecule profiles of the fermented milk, were recorded. The strains were further tested for their anti-Listeria monocytogenes activity in milk. The data obtained highlighted good potential for some of the tested strains, which showed production of nisin beginning within 12 h after the inoculation and reaching maximum levels between 24 and 48 h. The highest inactivation levels of L. monocytogenes in milk was reached in the presence of the strains 101877/1, LBG2, 9FS16, 11FS16, 3LC39, FBG1P, UL36, UL720, UL35. The strains generated in milk-specific volatile profiles and differences in the presence of fundamental aromatic molecules of dairy products, such as 2-butanone and diacetyl. The results highlight the interesting potential of some L. lactis strains, the producer of nisin, to be further used as biocontrol agents, although the strains need to be tested for interaction with traditional thermophilic starters and tested in real cheesemaking conditions

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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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)

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the HERWIG7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG7, and are obtained from a fit to minimum-bias data collected by the CMS experiment at s=0.9, 7, and 13Te. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the dat

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%

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Impact of process conditions on probiotic survival and physicochemical characteristics of fermented milk containing functional vaginal strains

Functional foods are considered a promising dietary strategy to reduce incidence of human illness thanks to their active components. The project FUNPRO-L wants to develop a probiotic fermented milk designed to be good, from a sensory perspective, healthy and functional since made with exopolysaccharides-producing lactic acid bacteria and vaginal probiotics. First, acidification kinetics were determined by applying 1 or 3U of the commercial starter Lyofast ST440 (Sacco) in skimmed milk incubated at 45°C for up to 24h. 4.5 and 7h of fermentation already dropped the pH to around 5 and 4.5, respectively. Therefore, these two incubation times and 1U of the starter culture were independently tested with 5 different vaginal probiotics (Lactobacillus crispatus BC1, BC4 and BC5; Lactobacillus gasseri BC9 and BC12), previously characterized for their functional properties, supplemented at 7 and 8 Log CFU/ml. pH, starter culture and probiotics viability, water holding capacity (WHC), and volatile molecule profiles of the fermented products were evaluated after 0 and 28 days of storage at 5°C. After 28 days of storage, control samples which underwent to 7 and 4.5h of fermentation showed a pH of 4.0 and 4.5, respectively. Addition of vaginal strains, especially at 8 Log CFU/ml, determined a further reduction of the pH up to 3.84 (7h) and 4.07 (4.5h) with BC5 and BC9, respectively. A drop of about 1 and 0.5 Log CFU/ml of the probiotics and the starter culture were observed in all the samples fermented for 7h and 4.5h, respectively. WHC increased after fermentation with vaginal strains, while it was maintained or reduced upon 28 days of storage, depending on the probiotic applied. The analyses of the volatile compounds showed specific fingerprints for each strain and concentration used. This preliminary screening provided the basis for the production and formulation of a fermented milk, containing functional probiotics, intended to promote female well-being

Human Breast Milk: A Source of Potential Probiotic Candidates

This study focuses on the isolation of lactobacilli/bifidobacteria from human breast milk and their first characterization, in the perspective to find new probiotic candidates to be included in food products. More specifically, breast-milk-isolated strains demonstrated a very good aptitude to adhere to intestinal cells, in comparison with L. rhamnosus GG strain, taken as reference. The same behavior has been found for hydrophobicity/auto-aggregation properties. A remarkable antagonistic activity was detected for these isolates not only against spoilage and pathogenic species of food interest, but also against the principal etiological agents of intestinal infections. Indeed, isolated strains impaired spoilage and pathogenic species growth, as well as biofilm formation by gut pathogens. In addition, breast milk strains were characterized for their antibiotic susceptibility, displaying species-specific and strain-specific susceptibility patterns. Finally, to assess their technological potential, the fermentation kinetics and viability of breast milk strains in pasteurized milk were investigated, also including the study of the volatile molecule profiles. In this regard, all the strains pointed out the release of aroma compounds frequently associated with the sensory quality of several dairy products such as acetic acid, diacetyl, acetoin, acetaldehyde. Data here reported point up the high potential of breast-milk-isolated strains as probiotics