A selected core microbiome drives the early stages of three popular italian cheese manufactures

Microbial composition and viability of natural whey starters used in PDO Comté cheese-making

Natural whey starters (NWS) are cultures with undefined multiple-strains species commonly used to speed up the fermentation process of cheeses. The aim of this study was to explore the diversity and the viability of Comté cheese NWS microbiota. Culture-dependent methods, i.e. plate counting and genotypic characterization, and culture-independent methods, i.e. qPCR, viability-qPCR, fluorescence microscopy and DNA metabarcoding, were combined to analyze thirty-six NWS collected in six Comté cheese factories at two seasons. Our results highlighted that NWS were dominated by Streptococcus thermophilus (ST) and thermophilic lactobacilli. These species showed a diversity of strains based on Rep-PCR. The dominance of Lactobacillus helveticus (LH) over Lactobacillus delbrueckii (LD) varied depending on the factory and the season. This highlighted two types of NWS: the type-ST/LD (LD > LH) and the type-ST/LH (LD < LH). The microbial composition varied depending on cheese factory. One factory was distinguished by its level of culturable microbial groups (ST, enterococci and yeast) and its fungi diversity. The approaches used to estimate the viability showed that most NWS cells were viable. Further investigations are needed to understand the microbial diversity of these NWS.

An integrated approach to explore the microbial biodiversity of natural milk cultures for cheesemaking

The use of natural milk culture (NMC) represents a key factor in Protected Designation of Origin (PDO) Montasio cheese, contributing to its distinctive sensory profile. The complex microbial ecosystem of NMC is the result of heat treatment and incubation conditions, which can vary considerably among different production plants. In this study, the microbiota of NMC collected from 10 PDO Montasio cheese dairies was investigated by employing colony counts and metagenomic analysis. Furthermore, residual sugars, organic acids, and volatile profiles were quantitatively investigated. Results showed that Streptococcus thermophilus was the dominant species in all NMC, and a subdominant population made of other streptococci and Ligilactobacillus salivarius was also present. The incubation temperature appeared to be the main driver of biodiversity in NMC. Metagenomics allowed us to evidence the presence of minor species involving safety (e.g., Staphylococcus aureus) as well as possible functional aspects (Next Generation Probiotics). Statistical analysis based on residual sugars, organic acids, and volatiles' content allowed to correlate the presence of specific microbial groups with metabolites of great technological and sensory relevance, which can contribute to giving value to the artisanal production procedures of NMC and clarify their role in the creation of the characteristics of PDO Montasio cheese.

Severity-Dependent Interhemispheric White Matter Connectivity Predicts Poststroke Neglect Recovery

Left-sided spatial neglect is a very common and challenging issue after right-hemispheric stroke, which strongly and negatively affects daily living behavior and recovery of stroke survivors. The mechanisms underlying recovery of spatial neglect remain controversial, particularly regarding the involvement of the intact, contralesional hemisphere, with potential contributions ranging from maladaptive to compensatory. In the present prospective, observational study, we assessed neglect severity in 54 right-hemispheric stroke patients (32 male; 22 female) at admission to and discharge from inpatient neurorehabilitation. We demonstrate that the interaction of initial neglect severity and spared white matter (dis)connectivity resulting from individual lesions (as assessed by diffusion tensor imaging, DTI) explains a significant portion of the variability of poststroke neglect recovery. In mildly impaired patients, spared structural connectivity within the lesioned hemisphere is sufficient to attain good recovery. Conversely, in patients with severe impairment, successful recovery critically depends on structural connectivity within the intact hemisphere and between hemispheres. These distinct patterns, mediated by their respective white matter connections, may help to reconcile the dichotomous perspectives regarding the role of the contralesional hemisphere as exclusively compensatory or not. Instead, they suggest a unified viewpoint wherein the contralesional hemisphere can - but must not necessarily - assume a compensatory role. This would depend on initial impairment severity and on the available, spared structural connectivity. In the future, our findings could serve as a prognostic biomarker for neglect recovery and guide patient-tailored therapeutic approaches.

Chemoproteomics reveals immunogenic and tumor-associated cell surface substrates of ectokinase CK2α

New epitopes for immune recognition provide the basis of anticancer immunity. Due to the high concentration of extracellular adenosine triphosphate in the tumor microenvironment, we hypothesized that extracellular kinases (ectokinases) could have dysregulated activity and introduce aberrant phosphorylation sites on cell surface proteins. We engineered a cell-tethered version of the extracellular kinase CK2α, demonstrated it was active on cells under tumor-relevant conditions, and profiled its substrate scope using a chemoproteomic workflow. We then demonstrated that mice developed polyreactive antisera in response to syngeneic tumor cells that had been subjected to surface hyperphosphorylation with CK2α. Interestingly, these mice developed B cell and CD4+ T cell responses in response to these antigens but failed to develop a CD8+ T cell response. This work provides a workflow for probing the extracellular phosphoproteome and demonstrates that extracellular phosphoproteins are immunogenic even in a syngeneic system.

Evaluating generalizability of artificial intelligence models for molecular datasets

Deep learning has made rapid advances in modeling molecular sequencing data. Despite achieving high performance on benchmarks, it remains unclear to what extent deep learning models learn general principles and generalize to previously unseen sequences. Benchmarks traditionally interrogate model generalizability by generating metadata based (MB) or sequence-similarity based (SB) train and test splits of input data before assessing model performance. Here, we show that this approach mischaracterizes model generalizability by failing to consider the full spectrum of cross-split overlap, i.e., similarity between train and test splits. We introduce Spectra, a spectral framework for comprehensive model evaluation. For a given model and input data, Spectra plots model performance as a function of decreasing cross-split overlap and reports the area under this curve as a measure of generalizability. We apply Spectra to 18 sequencing datasets with associated phenotypes ranging from antibiotic resistance in tuberculosis to protein-ligand binding to evaluate the generalizability of 19 state-of-the-art deep learning models, including large language models, graph neural networks, diffusion models, and convolutional neural networks. We show that SB and MB splits provide an incomplete assessment of model generalizability. With Spectra, we find as cross-split overlap decreases, deep learning models consistently exhibit a reduction in performance in a task- and model-dependent manner. Although no model consistently achieved the highest performance across all tasks, we show that deep learning models can generalize to previously unseen sequences on specific tasks. Spectra paves the way toward a better understanding of how foundation models generalize in biology.

Tools and methods for high-throughput single-cell imaging with the mother machine

Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely-used image analysis pipelines, including BACMMAN and DeLTA. Researchers often analyze mother machine data with custom scripts using varied image analysis methods, but a quantitative comparison of the output of different pipelines has been lacking. To this end, we show that key single-cell physiological parameter correlations and distributions are robust to the choice of analysis method. However, we also find that small changes in thresholding parameters can systematically alter parameters extracted from single-cell imaging experiments. Moreover, we explicitly show that in deep learning based segmentation, "what you put is what you get" (WYPIWYG) - i.e., pixel-level variation in training data for cell segmentation can propagate to the model output and bias spatial and temporal measurements. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over the last decade in our lab, we also provide information for those who want to implement mother-machine-based high-throughput imaging and analysis methods in their research.

Long-term gut colonization with ESBL-producing Escherichia coli in participants without known risk factors from the southeastern United States

We evaluated gut carriage of extended spectrum beta lactamase producing Enterobacteriaceae (ESBL-E) in southeastern U.S. residents without recent in-patient healthcare exposure. Study enrollment was January 2021-February 2022 in Athens, Georgia, U.S. and included a diverse population of 505 adults plus 50 child participants (age 0-5). Based on culture-based screening of stool samples, 4.5% of 555 participants carried ESBL-Es. This is slightly higher than reported in studies conducted 2012-2015, which found carriage rates of 2.5-3.9% in healthy U.S. residents. All ESBL-E confirmed isolates (n=25) were identified as Escherichia coli. Isolates belonged to 11 sequence types, with 48% classified as ST131. Ninety six percent of ESBL-E isolates carried a blaCTX-M gene. Isolated ESBL-Es frequently carried virulence genes as well as multiple classes of antibiotic resistance genes. Long-term colonization was common, with 64% of ESBL-E positive participants testing positive when rescreened three months later. One participant yielded isolates belonging to two different E. coli sequence types that carried blaCTX-M-1 genes on near-identical plasmids, suggesting intra-gut plasmid transfer. Isolation of E. coli on media without antibiotics revealed that ESBL-E. coli typically made up a minor fraction of the overall gut E. coli population, although in some cases they were the dominant strain. ESBL-E carriage was not associated with a significantly different stool microbiome composition. However, some microbial taxa were differentially abundant in ESBL-E carriers. Together, these results suggest that a small subpopulation of US residents are long-term, asymptomatic carriers of ESBL-Es, and may serve as an important reservoir for community spread of these ESBL genes.

Metagenomic Insights into the Taxonomic and Functional Features of Traditional Fermented Milk Products from Russia

Fermented milk products (FMPs) contain probiotics that are live bacteria considered to be beneficial to human health due to the production of various bioactive molecules. In this study, nine artisanal FMPs (kefir, ayran, khurunga, shubat, two cottage cheeses, bryndza, khuruud and suluguni-like cheese) from different regions of Russia were characterized using metagenomics. A metagenomic sequencing of ayran, khurunga, shubat, khuruud and suluguni-like cheese was performed for the first time. The taxonomic profiling of metagenomic reads revealed that Lactococcus species, such as Lc. lactis and Lc. cremoris prevailed in khuruud, bryndza, one sample of cottage cheese and khurunga. The latter one together with suluguni-like cheese microbiome was dominated by bacteria, affiliated to Lactobacillus helveticus (32-35%). In addition, a high proportion of sequences belonging to the genera Lactobacillus, Lactococcus and Streptococcus but not classified at the species level were found in the suluguni-like cheese. Lactobacillus delbrueckii, as well as Streptococcus thermophilus constituted the majority in another cottage cheese, kefir and ayran metagenomes. The microbiome of shubat, produced from camel's milk, was significantly distinctive, and Lentilactobacillus kefiri, Lactobacillus kefiranofaciens and Bifidobacterium mongoliense represented the dominant components (42, 7.4 and 5.6%, respectively). In total, 78 metagenome-assembled genomes with a completeness ≥ 50.2% and a contamination ≤ 8.5% were recovered: 61 genomes were assigned to the Enterococcaceae, Lactobacillaceae and Streptococcaceae families (the Lactobacillales order within Firmicutes), 4 to Bifidobacteriaceae (the Actinobacteriota phylum) and 2 to Acetobacteraceae (the Proteobacteria phylum). A metagenomic analysis revealed numerous genes, from 161 to 1301 in different products, encoding glycoside hydrolases and glycosyltransferases predicted to participate in lactose, alpha-glucans and peptidoglycan hydrolysis as well as exopolysaccharides synthesis. A large number of secondary metabolite biosynthetic gene clusters, such as lanthipeptides, unclassified bacteriocins, nonribosomal peptides and polyketide synthases were also detected. Finally, the genes involved in the synthesis of bioactive compounds like β-lactones, terpenes and furans, nontypical for fermented milk products, were also found. The metagenomes of kefir, ayran and shubat was shown to contain either no or a very low count of antibiotic resistance genes. Altogether, our results show that traditional indigenous fermented products are a promising source of novel probiotic bacteria with beneficial properties for medical and food industries.

Regulation of Chromatin Architecture by Transcription Factor Binding

Transcription factors (TF) bind to chromatin and regulate the expression of genes. The pair Myc:Max binds to E-box regulatory DNA elements throughout the genome, controlling transcription of a large group of specific genes. We introduce an implicit modeling protocol for Myc:Max binding to mesoscale chromatin fibers to determine TF effect on chromatin architecture and shed light on its mechanism of gene regulation. We first bind Myc:Max to different chromatin locations and show how it can direct fiber folding and formation of microdomains, and how this depends on the linker DNA length. Second, by simulating increasing concentrations of Myc:Max binding to fibers that differ in the DNA linker length, linker histone density, and acetylation levels, we assess the interplay between Myc:Max and other chromatin internal parameters. Third, we study the mechanism of gene silencing by Myc:Max binding to the Eed gene loci. Overall, our results show how chromatin architecture can be regulated by TF binding. The position of TF binding dictates the formation of microdomains that appear visible only at the ensemble level. On the other hand, the presence of linker histone, acetylations, or different linker DNA lengths regulates the concentration-dependent effect of TF binding. Furthermore, we show how TF binding can repress gene expression by increasing fiber folding motifs that help compact and occlude the promoter region. Importantly, this effect can be reversed by increasing linker histone density. Overall, these results shed light on the epigenetic control of the genome dictated by TF binding.

Synthetic mucus barrier arrays as a nanoparticle formulation screening platform

A mucus gel layer lines the luminal surface of tissues throughout the body to protect them from infectious agents and particulates. As a result, nanoparticle drug delivery systems delivered to these sites may become trapped in mucus and subsequently cleared before they can reach target cells. As such, optimizing the properties of nanoparticle delivery vehicles, such as their surface chemistry and size, is essential to improving their penetration through the mucus barrier. In previous work, we developed a mucin-based hydrogel that has viscoelastic properties like that of native mucus which can be further tailored to mimic specific mucosal tissues and disease states. Using this biomimetic hydrogel system, a 3D-printed array containing synthetic mucus barriers was created that is compatible with a 96-well plate enabling its use as a high-throughput screening platform for nanoparticle drug delivery applications. To validate this system, we evaluated several established design parameters to determine their impact on nanoparticle penetration through synthetic mucus barriers. Consistent with the literature, we found nanoparticles of smaller size and coated with a protective PEG layer more efficiently penetrated through synthetic mucus barriers. In addition, we evaluated a mucolytic (tris (2-carboxyethyl) phosphine, TCEP) for use as a permeation enhancer for mucosal drug delivery. In comparison to N-acetyl cysteine (NAC), we found TCEP significantly improved nanoparticle penetration through a disease-like synthetic mucus barrier. Overall, our results establish a new high-throughput screening approach using synthetic mucus barrier arrays to identify promising nanoparticle formulation strategies for drug delivery to mucosal tissues.

Global patterns in gene content of soil microbiomes emerge from microbial interactions

Microbial metabolism sustains life on Earth. Sequencing surveys of communities in hosts, oceans, and soils have revealed ubiquitous patterns linking the microbes present, the genes they possess, and local environmental conditions. One prominent explanation for these patterns is environmental filtering: local conditions select strains with particular traits. However, filtering assumes ecological interactions do not influence patterns, despite the fact that interactions can and do play an important role in structuring communities. Here, we demonstrate the insufficiency of the environmental filtering hypothesis for explaining global patterns in topsoil microbiomes. Using denitrification as a model system, we find that the abundances of two characteristic genotypes trade-off with pH; nar gene abundances increase while nap abundances decrease with declining pH. Contradicting the filtering hypothesis, we show that strains possessing the Nar genotype are enriched in low pH conditions but fail to grow alone. Instead, the dominance of Nar genotypes at low pH arises from an ecological interaction with Nap genotypes that alleviates nitrite toxicity. Our study provides a roadmap for dissecting how global associations between environmental variables and gene abundances arise from environmentally modulated community interactions.

Human trophoblast stem cells can be used to model placental susceptibility to Toxoplasma gondii and highlight the critical importance of the trophoblast cell surface in pathogen resistance

The placenta is a critical barrier against viral, bacterial, and eukaryotic pathogens. For most teratogenic pathogens, the precise molecular mechanisms of placental resistance are still being unraveled. Given the importance to understand these mechanisms and challenges in replicating trophoblast- pathogen interactions using in vitro models, we tested an existing stem-cell derived model of trophoblast development for its relevance to infection with Toxoplasma gondii . We grew human trophoblast stem cells (TS CT ) under conditions leading to either syncytiotrophoblast (TS SYN ) or cytotrophoblast (TS CYT ) and infected them with T. gondii . We evaluated T. gondii proliferation and invasion, cell ultrastructure, as well as for transcriptome changes after infection. TS SYNs cells showed similar ultrastructure compared to primary cells and villous explants when analyzed by TEM and SEM, a resistance to T. gondii adhesion could be visualized on the SEM level. Furthermore, TS SYNs were highly refractory to parasite adhesion and replication, while TS CYT were not. RNA-seq data on mock-treated and infected cells identified differences between cell types as well as how they responded to T. gondii infection. We also evaluated if TS SC -derived SYNs and CYTs had distinct resistance profiles to another vertically transmitted facultative intracellular pathogen, Listeria monocytogenes . We demonstrate that TS SYNs are highly resistant to L. monocytogenes , while TS CYTs are not. Like T. gondii , TS SYN resistance to L. monocytogenes was at the level of bacterial adhesion. Altogether, our data indicate that stem-cell derived trophoblasts recapitulate resistance profiles of primary cells to T. gondii and highlight the critical importance of the placental surface in cell-autonomous resistance to teratogens.

Fluctuating landscapes and heavy tails in animal behavior

Animal behavior is shaped by a myriad of mechanisms acting on a wide range of scales. This immense variability hampers quantitative reasoning and renders the identification of universal principles elusive. Through data analysis and theory, we here show that slow non-ergodic drives generally give rise to heavy-tailed statistics in behaving animals. We leverage high-resolution recordings of C. elegans locomotion to extract a self-consistent reduced order model for an inferred reaction coordinate, bridging from sub-second chaotic dynamics to long-lived stochastic transitions among metastable states. The slow mode dynamics exhibits heavy-tailed first passage time distributions and correlation functions, and we show that such heavy tails can be explained by dynamics on a time-dependent potential landscape. Inspired by these results, we introduce a generic model in which we separate faster mixing modes that evolve on a quasi-stationary potential, from slower non-ergodic modes that drive the potential landscape, and reflect slowly varying internal states. We show that, even for simple potential landscapes, heavy tails emerge when barrier heights fluctuate slowly and strongly enough. In particular, the distribution of first passage times and the correlation function can asymptote to a power law, with related exponents that depend on the strength and nature of the fluctuations. We support our theoretical findings through direct numerical simulations.

ECM-Focused Proteomic Analysis of Ear Punch Regeneration in Acomys Cahirinus

In mammals, significant injury is generally followed by the formation of a fibrotic scar which provides structural integrity but fails to functionally restore damaged tissue. Spiny mice of the genus Acomys represent the first example of full skin autotomy in mammals. Acomys cahirinus has evolved extremely weak skin as a strategy to avoid predation and is able to repeatedly regenerate healthy tissue without scar after severe skin injury or full-thickness ear punches. Extracellular matrix (ECM) composition is a critical regulator of wound repair and scar formation and previous studies have suggested that alterations in its expression may be responsible for the differences in regenerative capacity observed between Mus musculus and A. cahirinus , yet analysis of this critical tissue component has been limited in previous studies by its insolubility and resistance to extraction. Here, we utilize a 2-step ECM-optimized extraction to perform proteomic analysis of tissue composition during wound repair after full-thickness ear punches in A. cahirinus and M. musculus from weeks 1 to 4 post-injury. We observe changes in a wide range of ECM proteins which have been previously implicated in wound regeneration and scar formation, including collagens, coagulation and provisional matrix proteins, and matricryptic signaling peptides. We additionally report differences in crosslinking enzyme activity and ECM protein solubility between Mus and Acomys. Furthermore, we observed rapid and sustained increases in CD206, a marker of pro-regenerative M2 macrophages, in Acomys, whereas little or no increase in CD206 was detected in Mus. Together, these findings contribute to a comprehensive understanding of tissue cues which drive the regenerative capacity of Acomys and identify a number of potential targets for future pro-regenerative therapies.

Striatal dopamine tone is positively associated with body mass index in humans as determined by PET using dual dopamine type-2 receptor antagonist tracers

The relationship between adiposity and dopamine type-2 receptor binding potential (D2BP) in the human brain has been repeatedly studied for >20 years with highly discrepant results, likely due to variable methodologies and differing study populations. We conducted a controlled inpatient feeding study to measure D2BP in the striatum using positron emission tomography with both [18F]fallypride and [11C]raclopride in pseudo-random order in 54 young adults with a wide range of body mass index (BMI 20-44 kg/m2). Within-subject D2BP measurements using the two tracers were moderately correlated (r=0.47, p<0.001). D2BP was negatively correlated with BMI as measured by [11C]raclopride (r= -0.51; p<0.0001) but not [18F]fallypride (r=-0.01; p=0.92) and these correlation coefficients were significantly different from each other (p<0.001). Given that [18F]fallypride has greater binding affinity to dopamine type-2 receptors than [11C]raclopride, which is more easily displaced by endogenous dopamine, our results suggest that adiposity is positively associated with increased striatal dopamine tone.

Division of labor among H3K4 Methyltransferases Defines Distinct Facets of Homeostatic Plasticity

Heterozygous mutations in any of the six H3K4 methyltransferases (KMT2s) result in monogenic neurodevelopmental disorders, indicating nonredundant yet poorly understood roles of this enzyme family in neurodevelopment. Recent evidence suggests that histone methyltransferase activity may not be central to KMT2 functions; however, the enzymatic activity is evolutionarily conserved, implicating the presence of selective pressure to maintain the catalytic activity. Here, we show that H3K4 methylation is dynamically regulated during prolonged alteration of neuronal activity. The perturbation of H3K4me by the H3.3K4M mutant blocks synaptic scaling, a form of homeostatic plasticity that buffers the impact of prolonged reductions or increases in network activity. Unexpectedly, we found that the six individual enzymes are all necessary for synaptic scaling and that the roles of KMT2 enzymes segregate into evolutionary-defined subfamilies: KMT2A and KMT2B (fly-Trx homologs) for synaptic downscaling, KMT2C and KMT2D (Trr homologs) for upscaling, and KMT2F and KMT2G (dSet homologs) for both directions. Selective blocking of KMT2A enzymatic activity by a small molecule and targeted disruption of the enzymatic domain both blocked the synaptic downscaling and interfered with the activity-dependent transcriptional program. Furthermore, our study revealed specific phases of synaptic downscaling, i.e., induction and maintenance, in which KMT2A and KMT2B play distinct roles. These results suggest that mammalian brains have co-opted intricate H3K4me installation to achieve stability of the expanding neuronal circuits.

Whole blood mitochondrial copy number in clinical populations with mood disorders: a meta-analysis

Background

Major depressive disorder (MDD) and bipolar disorder (BD), are globally prevalent, contributing to significant disease burden and adverse health outcomes. These mood disorders are associated with changes in many aspects of brain reward pathways, yet cellular and molecular changes in the brain are not readily available in clinical populations. Therefore, the use of biomarkers as proxies for changes in the brain are necessary. The proliferation of mitochondria in blood has emerged as a potentially useful biomarker, yet a clear consensus on how these mood disorders impact mitochondrial DNA copy number (mtDNAcn) has not been reached.

Methods

Following PRISMA guidelines for a systematic search, 22 papers met inclusion criteria for meta-analysis (10 MDD, 10 BD, 2 both MDD and BD). We extracted demographic, disorder, and methodological information with mtDNAcn. Using the metafor package for R, calculated effect sizes were used in random effects or meta regression models for MDD and BD.

Results

Our results show a trending increase in mtDNAcn in patients with MDD, which reaches significance when one study with outlying demographic characteristics is excluded. Overall, there was no effect of BD on mtDNAcn, however, further subgroup and meta-regression analysis indicated the effects on mtDNAcn are dependent on BD type.

Conclusions

Together our data suggest whole blood/leukocyte mtDNAcn may be a useful biomarker for mood disorders, with MDD and BD Type II associated with higher mtDNAcn, and BD Type I associated with lower mtDNAcn. Further study of blood mtDNAcn could predict downstream health outcomes or treatment responsivity in individuals with mood disorders.

Engineering Quorum Quenching Acylases with Improved Kinetic and Biochemical Properties

Many Gram-negative bacteria respond to N-acyl-L-homoserine lactone (AHL) signals to coordinate phenotypes such as biofilm formation and virulence factor production. Quorum-quenching enzymes, such as acylases, chemically degrade AHL signals, prevent signal reception by bacteria, and inhibit undesirable traits related to biofilm. These capabilities make these enzymes appealing candidates for controlling microbes. Yet, enzyme candidates with high activity levels, high substrate specificity for specific interference, and that are capable of being formulated into materials are needed. In this work, we undertook engineering efforts against two AHL acylases, PvdQ and MacQ, to obtain improved acylase variants. The engineering of acylase is complicated by low-throughput enzymatic assays. To alleviate this challenge, we report a time-course kinetic assay for AHL acylase that tracks the real-time production of homoserine lactone. Using the protein one-stop shop server (PROSS), we identified variants of PvdQ that were significantly stabilized, with melting point increases of up to 13.2 °C, which translated into high resistance against organic solvents and increased compatibility with material coatings. We also generated mutants of MacQ with considerably improved kinetic properties, with >10-fold increases against N-butyryl-L-homoserine lactone and N-hexanoyl-L-homoserine lactone. In fact, the variants presented here exhibit unique combinations of stability and activity levels. Accordingly, these changes resulted in increased quenching abilities using a biosensor model and greater inhibition of virulence factor production of Pseudomonas aeruginosa PA14. While the crystal structure of one of the MacQ variants, M1, did not reveal obvious structural determinants explaining the observed changes in kinetics, it allowed for the capture of an acyl-enzyme intermediate that confirms a previously hypothesized catalytic mechanism of AHL acylases.

Microglia mediate contact-independent neuronal pruning via secreted Neuraminidase-3 associated with extracellular vesicles

Neurons communicate with each other through electrochemical transmission at synapses. Microglia, the resident immune cells of the central nervous system, can prune these synapses through a variety of contact-dependent and -independent means. Microglial secretion of active sialidase enzymes upon exposure to inflammatory stimuli is one unexplored mechanism of pruning. Recent work from our lab showed that treatment of neurons with bacterial sialidases disrupts neuronal network connectivity. Here, we find that activated microglia secrete Neuraminidase-3 (Neu3) associated with fusogenic extracellular vesicles. Furthermore, we show Neu3 mediates contact-independent pruning of neurons and subsequent disruption of neuronal networks through neuronal glycocalyx remodeling. We observe that NEU3 is transcriptionally upregulated upon exposure to inflammatory stimuli, and that a genetic knock-out of NEU3 abrogates the sialidase activity of inflammatory microglial secretions. Moreover, we demonstrate that Neu3 is associated with a subpopulation of extracellular vesicles, possibly exosomes, that are secreted by microglia upon inflammatory insult. Finally, we demonstrate that Neu3 is both necessary and sufficient to both desialylate neurons and decrease neuronal network connectivity. These results implicate Neu3 in remodeling of the glycocalyx leading to aberrant network-level activity of neurons, with implications in neuroinflammatory diseases such as Parkinson's disease and Alzheimer's disease.

The microbiota of Mozzarella di Bufala Campana PDO cheese: a study across the manufacturing process

Introduction

Mozzarella di Bufala Campana PDO cheese (MBC) is a globally esteemed Italian cheese. The traditional cheesemaking process of MBC relies on natural whey starter culture, water buffalo's milk, and the local agroecosystem.

Methods

In this study, the microbial ecology of intermediate samples of MBC production, coming from two dairies with slightly different cheesemaking technology (dairy M large producer, and dairy C medium-small), was investigated using 16S rRNA amplicon sequencing. This research aimed to provide insights into the dynamics of microbial consortia involved in various cheesemaking steps.

Results and discussion

All samples, except for raw buffalo milk, exhibited a core microbiome predominantly composed of Streptococcus spp. and Lactobacillus spp., albeit with different ratios between the two genera across the two MBC producers. Notably, the microbiota of the brine from both dairies, analyzed using 16S amplicon sequencing for the first time, was dominated by the Lactobacillus and Streptococcus genera, while only dairy C showed the presence of minor genera such as Pediococcus and Lentilactobacillus. Intriguingly, the final mozzarella samples from both producers displayed an inversion in the dominance of Lactobacillus spp. over Streptococcus spp. in the microbiota compared to curd samples, possibly attributable to the alleviation of thermal stress following the curd stretching step. In conclusion, the different samples from the two production facilities did not exhibit significant differences in terms of the species involved in MBC cheesemaking. This finding confirms that the key role in the MBC cheesemaking process lies with a small-sized microbiome primarily composed of Streptococcus and Lactobacillus spp.

Neural representation of phonological wordform in bilateral posterior temporal cortex

While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words evoke activation of a variety of representations (e.g., segmental, semantic, articulatory) in addition to form-based representations. We addressed these challenges through a novel integrated neural decoding and effective connectivity design using region of interest (ROI)-based, source reconstructed magnetoencephalography/electroencephalography (MEG/EEG) data collected during a lexical decision task. To localize wordform representations, we trained classifiers on words and nonwords from different phonological neighborhoods and then tested the classifiers' ability to discriminate between untrained target words that overlapped phonologically with the trained items. Training with either word or nonword neighbors supported decoding in many brain regions during an early analysis window (100-400 ms) reflecting primarily incremental phonological processing. Training with word neighbors, but not nonword neighbors, supported decoding in a bilateral set of temporal lobe ROIs, in a later time window (400-600 ms) reflecting activation related to word recognition. These ROIs included bilateral posterior temporal regions implicated in wordform representation. Effective connectivity analyses among regions within this subset indicated that word-evoked activity influenced the decoding accuracy more than nonword-evoked activity did. Taken together, these results evidence functional representation of wordforms in bilateral temporal lobes isolated from phonemic or semantic representations.

Analysing the dynamics of the bacterial community in pozol, a Mexican fermented corn dough

Pozol is a traditional prehispanic Mexican beverage made from fermented nixtamal dough; it is still part of everyday life in many communities due to its nutritional properties. It is the product of spontaneous fermentation and has a complex microbiota composed primarily of lactic acid bacteria (LAB). Although this is a beverage that has been used for centuries, the microbial processes that participate in this fermented beverage are not well understood. We fermented corn dough to produce pozol and sampled it at four key times to follow the community and metabolic changes (0, 9 24 and 48 h) by shotgun metagenomic sequencing to determine structural changes in the bacterial community, as well as metabolic genes used for substrate fermentation, nutritional properties and product safety. We found a core of 25 abundant genera throughout the 4 key fermentation times, with the genus Streptococcus being the most prevalent throughout fermentation. We also performed an analysis focused on metagenomic assembled genomes (MAGs) to identify species from the most abundant genera. Genes involving starch, plant cell wall (PCW), fructan and sucrose degradation were found throughout fermentation and in MAGs, indicating the metabolic potential of the pozol microbiota to degrade these carbohydrates. Complete metabolic modules responsible for amino acid and vitamin biosynthesis increased considerably during fermentation, and were also found to be abundant in MAG, highlighting the bacterial contribution to the well-known nutritional properties attributed to pozol. Further, clusters of genes containing CAZymes (CGCs) and essential amino acids and vitamins were found in the reconstructed MAGs for abundant species in pozol. The results of this study contribute to our understanding of the metabolic role of micro-organisms in the transformation of corn to produce this traditional beverage and their contribution to the nutritional impact that pozol has had for centuries in the traditional cuisine of southeast Mexico.

Selective enrichment of the raw milk microbiota in cheese production: Concept of a natural adjunct milk culture

In cheese production, microorganisms are usually added at the beginning of the process as primary starters to drive curd acidification, while secondary microorganisms, with other pro-technological features important for cheese ripening, are added as selected cultures. This research aimed to investigate the possibilities of influencing and selecting the raw milk microbiota using artisanal traditional methods, providing a simple method to produce a natural supplementary culture. We investigated the production of an enriched raw milk whey culture (eRWC), a natural adjunct microbial culture produced from mixing an enriched raw milk (eRM) with a natural whey culture (NWC). The raw milk was enriched by spontaneous fermentation for 21 d at 10°C. Three milk enrichment protocols were tested: heat treatment before incubation, heat treatment plus salt addition, and no treatment. The eRMs were then co-fermented with NWC (ratio of 1:10) at 38°C for 6 h (young eRWC) and 22 h (old eRWC). Microbial diversity during cultures' preparation was evaluated through the determination of colony forming units on selective growth media, and next-generation sequencing (16S rRNA gene amplicon sequencing). The enrichment step increased the streptococci and lactobacilli but reduced microbial richness and diversity of the eRMs. Although the lactic acid bacteria viable count was not significantly different between the eRWCs, they harbored higher microbial richness and diversity than NWC. Natural adjunct cultures were then tested in cheese making trials, following the microbial development, and assessing the chemical quality of the 120 d ripened cheeses. The use of eRWCs slowed the curd acidification in the first hours of cheese making but the pH 24 h after production settled to equal values for all the cheeses. Although the use of diverse eRWCs contributed to having a richer and more diverse microbiota in the early stages of cheese making, their effect decreased over time during ripening, showing an inferior effect to the raw milk microbiota. Even if more research is needed, the optimization of such a tool could be an alternative to the practice of isolating, geno-pheno-typing, and formulating mixed-defined-strain adjunct cultures that require knowledge and facilities not always available for artisanal cheese makers.

A signature of pre-operative biomarkers of cellular senescence to predict risk of cardiac and kidney adverse events after cardiac surgery

Objective

Understand the potential for pre-operative biomarkers of cellular senescence, a primary aging mechanism, to predict risk of cardiac surgery-associated adverse events.

Methods

Biomarkers of senescence were assessed in blood samples collected prior to surgery in 331 patients undergoing CABG +/-valve repair or replacement. Patients were followed throughout the hospital stay and at a 30-day follow-up visit. Logistic regression models for pre-operative risk prediction were built for age-related clinical outcomes with high incidence including KDIGO-defined acute kidney injury (AKI), decline in eGFR ≥25% between pre-op and 30 days, and MACKE30, a composite endpoint of major adverse cardiac and kidney events at 30d.

Results

AKI occurred in 19.9% of patients, persistent decline in kidney function at 30d occurred in 11.0%, and MACKE30 occurred in 13.4%. A network of six biomarkers of senescence (p16, p14, LAG3, CD244, CD28 and suPAR) were able to identify patients at risk for AKI (AUC 0.76), kidney decline at 30d (AUC 0.73), and MACKE30 (AUC 0.71). Comparing the top and bottom tertiles of senescence-based risk models, patients in the top tertile had 7.8 (3.3-8.4) higher odds of developing AKI, 4.5 (1.6-12.6) higher odds of developing renal decline at 30d, and 5.7 (2.1-15.6) higher odds of developing MACKE30. All models remained significant when adjusted for clinical variables. Patients with kidney function decline at 30d were largely non-overlapping and clinically distinct from those who experienced AKI, suggesting a different etiology. Typical clinical factors that predispose to AKI (e.g., age, CKD, surgery type) associated with AKI but not the 30d decline endpoint which was instead associated with new-onset atrial fibrillation.

Conclusions

A six-member network of biomarkers of senescence, a fundamental mechanism of aging, can identify patients for risk of adverse kidney and cardiac events when measured pre-operatively.

Tensor decomposition based feature extraction and classification to detect natural selection from genomic data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under non-convex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data while preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx , which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Prospective Bidirectional Relations Between Depression and Metabolic Health: 30 Year Follow-up from the NHLBI CARDIA Study

Objective

This study investigated prospective bidirectional relationships between depression and metabolic syndrome (MetS), and the moderating effects of race, sex, and health behaviors in a diverse cohort followed for 30 years.

Methods

Data were analyzed from the NHLBI CARDIA study, a 30 year-prospective study of young adults (N = 5113; M age = 24.76 (SD = 3.63) at baseline; 45% male) who were tested every 5 years between 1985-2015. Measures included biological assessments of MetS components, and self-reported depressive symptoms based on the Center for Epidemiologic Studies Depression (CESD) scale. Data analyses included bi-directional general estimating equations analyses of time-lagged associations between depressive symptoms and MetS.

Results

There was a consistent, bi-directional relationship between depressive symptoms and MetS over time. Individuals with more CESD depressive symptoms were more likely to develop MetS over time compared to those reporting fewer symptoms (Wald Chi-Square = 7.09 (1), p < 0.008), and MetS was similarly predictive of CESD. MetS more consistently predicted depressive symptoms at each 5-year exam than depressive symptoms predicted MetS. Race and sex moderated relationships between depression and MetS, with White females, White individuals overall, and females overall demonstrating significant relationships. Health behaviors were not related to depression-MetS associations.

Conclusion

In a diverse young adult population prospectively followed into late middle age, MetS more consistently predicted depression over time than depression predicted MetS. The relation between MetS and depressive symptoms was moderated by race and sex, but not health behaviors.

Characterization of spatiotemporal dynamics of binary and graded tonic pain in humans using intracranial recordings

Pain is a complex experience involving sensory, emotional, and cognitive aspects, and multiple networks manage its processing in the brain. Examining how pain transforms into a behavioral response can shed light on the networks' relationships and facilitate interventions to treat chronic pain. However, studies using high spatial and temporal resolution methods to investigate the neural encoding of pain and its psychophysical correlates have been limited. We recorded from intracranial stereo-EEG (sEEG) electrodes implanted in sixteen different brain regions of twenty patients who underwent psychophysical pain testing consisting of a tonic thermal stimulus to the hand. Broadband high-frequency local field potential amplitude (HFA; 70-150 Hz) was isolated to investigate the relationship between the ongoing neural activity and the resulting psychophysical pain evaluations. Two different generalized linear mixed-effects models (GLME) were employed to assess the neural representations underlying binary and graded pain psychophysics. The first model examined the relationship between HFA and whether the patient responded "yes" or "no" to whether the trial was painful. The second model investigated the relationship between HFA and how painful the stimulus was rated on a visual analog scale. GLMEs revealed that HFA in the inferior temporal gyrus (ITG), superior frontal gyrus (SFG), and superior temporal gyrus (STG) predicted painful responses at stimulus onset. An increase in HFA in the orbitofrontal cortex (OFC), SFG, and striatum predicted pain responses at stimulus offset. Numerous regions including the anterior cingulate cortex, hippocampus, IFG, MTG, OFC, and striatum, predicted the pain rating at stimulus onset. However, only the amygdala and fusiform gyrus predicted increased pain ratings at stimulus offset. We characterized the spatiotemporal representations of binary and graded painful responses during tonic pain stimuli. Our study provides evidence from intracranial recordings that the neural encoding of psychophysical pain changes over time during a tonic thermal stimulus, with different brain regions being predictive of pain at the beginning and end of the stimulus.

Distinct Bacterial Communities in São Jorge Cheese with Protected Designation of Origin (PDO)

São Jorge cheese is an iconic product of the Azores, produced from raw cow's milk and natural whey starter (NWS). Although it is produced according to Protected Designation of Origin (PDO) specifications, the granting of the PDO label depends crucially on sensory evaluation by trained tasters. The aim of this work was to characterize the bacterial diversity of this cheese using next-generation sequencing (NGS) and to identify the specific microbiota that contributes most to its uniqueness as a PDO by distinguishing the bacterial communities of PDO and non-PDO cheeses. The NWS and curd microbiota was dominated by Streptococcus and Lactococcus, whereas Lactobacillus and Leuconostoc were also present in the core microbiota of the cheese along with these genera. Significant differences (p < 0.05) in bacterial community composition were found between PDO cheese and non-certified cheese; Leuconostoc was found to play the chief role in this regard. Certified cheeses were richer in Leuconostoc, Lactobacillus and Enterococcus, but had fewer Streptococcus (p < 0.05). A negative correlation was found between contaminating bacteria, e.g., Staphylococcus and Acinetobacter, and the development of PDO-associated bacteria such as Leuconostoc, Lactobacillus and Enterococcus. A reduction in contaminating bacteria was found to be crucial for the development of a bacterial community rich in Leuconostoc and Lactobacillus, thus justifying the PDO seal of quality. This study has helped to clearly distinguish between cheeses with and without PDO based on the composition of the bacterial community. The characterization of the NWS and the cheese microbiota can contribute to a better understanding of the microbial dynamics of this traditional PDO cheese and can help producers interested in maintaining the identity and quality of São Jorge PDO cheese.

Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes

The human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activity between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC well aligns with the observed FC when compared to that simulated with traditional structural connectome. Simulations were performed using the open source framework The Virtual Brain on High Performance Computing infrastructure.

Integrated Constraint-Based Modeling of E. coli Cell-Free Protein Synthesis

Cell-free protein expression has become a widely used research tool in systems and synthetic biology and a promising technology for protein biomanufacturing. Cell-free protein synthesis relies on in-vitro transcription and translation processes to produce a protein of interest. However, transcription and translation depend upon the operation of complex metabolic pathways for precursor and energy regeneration. Toward understanding the role of metabolism in a cell-free system, we developed a dynamic constraint-based simulation of protein production in the myTXTL E. coli cell-free system with and without electron transport chain inhibitors. Time-resolved absolute metabolite measurements for â"³ = 63 metabolites, along with absolute concentration measurements of the mRNA and protein abundance and measurements of enzyme activity, were integrated with kinetic and enzyme abundance information to simulate the time evolution of metabolic flux and protein production with and without inhibitors. The metabolic flux distribution estimated by the model, along with the experimental metabolite and enzyme activity data, suggested that the myTXTL cell-free system has an active central carbon metabolism with glutamate powering the TCA cycle. Further, the electron transport chain inhibitor studies suggested the presence of oxidative phosphorylation activity in the myTXTL cell-free system; the oxidative phosphorylation inhibitors provided biochemical evidence that myTXTL relied, at least partially, on oxidative phosphorylation to generate the energy required to sustain transcription and translation for a 16-hour batch reaction.

Universal drivers of cheese microbiomes

The culinary value, quality, and safety of cheese are largely driven by the resident bacteria, but comparative analyses of the cheese microbiota across cheese types are scarce. We present the first global synthesis of cheese microbiomes. Following a systematic literature review of cheese microbiology research, we collected 16S rRNA gene amplicon sequence data from 824 cheese samples spanning 58 cheese types and 16 countries. We found a consistent, positive relationship between microbiome richness and pH, and a higher microbial richness in cheeses derived from goat milk. In contrast, we found no relationship between pasteurization, geographic location, or salinity and richness. Milk and cheese type, geographic location, and pasteurization collectively explained 65% of the variation in microbial community composition. Importantly, we identified four universal cheese microbiome types, driven by distinct dominant taxa. Our study reveals notable diversity patterns among the cheese microbiota, which are driven by geography and local environmental variables.

Light and temperature regulate m6A-RNA modification to regulate growth in plants

N6-methyladenosine is a highly dynamic, abundant mRNA modification which is an excellent potential mechanism for fine tuning gene expression. Plants adapt to their surrounding light and temperature environment using complex gene regulatory networks. The role of m6A in controlling gene expression in response to variable environmental conditions has so far been unexplored. Here, we map the transcriptome-wide m6A landscape under various light and temperature environments. Identified m6A-modifications show a highly specific spatial distribution along transcripts with enrichment occurring in 5'UTR regions and around transcriptional end sites. We show that the position of m6A modifications on transcripts might influence cellular transcript localization and the presence of m6A-modifications is associated with alternative polyadenylation, a process which results in multiple RNA isoforms with varying 3'UTR lengths. RNA with m6A-modifications exhibit a higher preference for shorter 3'UTRs. These shorter 3'UTR regions might directly influence transcript abundance and localization by including or excluding cis-regulatory elements. We propose that environmental stimuli might change the m6A landscape of plants as one possible way of fine tuning gene regulation through alternative polyadenylation and transcript localization.

An Insight into Goat Cheese: The Tales of Artisanal and Industrial Gidotyri Microbiota

The purpose of this study was to determine for the first time the microbiota in artisanal-type and industrial-type Gidotyri cheeses and investigate the influence of the cheese-making practices on their composition using culture-independent techniques. The microbiota present in artisanal with commercial starters (Artisanal_CS, n = 15), artisanal with in-house starters (Artisanal_IHS, n = 10) and industrial (Ind., n = 9) Gidotyri cheese samples were analyzed using a targeted metagenomic approach (16S rRNA gene). The Ind. Gidotyri cheese microbiota were less complex, dominated by the Streptococcaceae family (91%) that was more abundant compared to the artisanal Gidotyri cheeses (p < 0.05). Artisanal cheeses were more diverse compositionally with specific bacterial species being prevalent to each subtype. Particularly, Loigolactobacillus coryniformis (OTU 175), Secundilactobacillus malefermentans (OTU 48), and Streptococcus parauberis (OTU 50) were more prevalent in Artisanal_IHS cheeses compared to Artisanal_CS (p ≤ 0.001) and Ind. (p < 0.01) Gidotyri cheeses. Carnobacterium maltaromaticum (OTU 23) and Enterobacter hormaechei subsp. hoffmannii (OTU 268) were more prevalent in Artisanal_CS cheeses compared to Artisanal_IHS cheeses (p < 0.05) and Ind. cheeses (p < 0.05). Hafnia alvei (OTU 13) and Acinetobacter colistiniresistens (OTU 111) tended to be more prevalent in Artisanal_CS compared to the other two cheese groups (p < 0.10). In conclusion, higher microbial diversity was observed in the artisanal-type Gidotyri cheeses, with possible bacterial markers specific to each subtype identified with potential application to traceability of the manufacturing processes’ authenticity and cheese quality.

Intraoperative Molecular Fluorescence Imaging of Pancreatic Cancer by Targeting Vascular Endothelial Growth Factor: A Multicenter Feasibility Dose-Escalation Study

Tumor visualization with near-infrared fluorescence (NIRF) imaging might aid exploration and resection of pancreatic cancer by visualizing the tumor in real time. Conjugation of the near-infrared fluorophore IRDye800CW to the monoclonal antibody bevacizumab enables targeting of vascular endothelial growth factor A. The aim of this study was to determine whether intraoperative tumor-specific imaging of pancreatic cancer with the fluorescent tracer bevacizumab-800CW is feasible and safe. Methods: In this multicenter dose-escalation phase I trial, patients in whom pancreatic ductal adenocarcinoma (PDAC) was suspected were administered bevacizumab-800CW (4.5, 10, or 25 mg) 3 d before surgery. Safety monitoring encompassed allergic or anaphylactic reactions and serious adverse events attributed to bevacizumab-800CW. Intraoperative NIRF imaging was performed immediately after laparotomy, just before and after resection of the specimen. Postoperatively, fluorescence signals on the axial slices and formalin-fixed paraffin-embedded tissue blocks from the resected specimens were correlated with histology. Subsequently, tumor-to-background ratios (TBR) were calculated. Results: Ten patients with clinically suspected PDAC were enrolled in the study. Four of the resected specimens were confirmed PDACs; other malignancies were distal cholangiocarcinoma, ampullary carcinoma, and neuroendocrine tumors. No serious adverse events were related to bevacizumab-800CW. In vivo tumor visualization with NIRF imaging differed per tumor type and was nonconclusive. Ex vivo TBRs were 1.3, 1.5, and 2.5 for the 4.5-, 10-, and 25-mg groups, respectively. Conclusion: NIRF-guided surgery in patients with suspected PDAC using bevacizumab-IRDye800CW is feasible and safe. However, suboptimal TBRs were obtained because no clear distinction between pancreatic cancer from normal or inflamed pancreatic tissue was achieved. Therefore, a more tumor-specific tracer than bevacizumab-IRDye800CW for PDAC is preferred.

Relationship between impaired BMP signalling and clinical risk factors at early-stage vascular injury in the preterm infant

INTRODUCTION

Chronic lung disease, that is, bronchopulmonary dysplasia (BPD) is the most common complication in preterm infants and develops as a consequence of the misguided formation of the gas-exchange area undergoing prenatal and postnatal injury. Subsequent vascular disease and its progression into pulmonary arterial hypertension critically determines long-term outcome in the BPD infant but lacks identification of early, disease-defining changes.

METHODS

We link impaired bone morphogenetic protein (BMP) signalling to the earliest onset of vascular pathology in the human preterm lung and delineate the specific effects of the most prevalent prenatal and postnatal clinical risk factors for lung injury mimicking clinically relevant conditions in a multilayered animal model using wild-type and transgenic neonatal mice.

RESULTS

We demonstrate (1) the significant reduction in BMP receptor 2 (BMPR2) expression at the onset of vascular pathology in the lung of preterm infants, later mirrored by reduced plasma BMP protein levels in infants with developing BPD, (2) the rapid impairment (and persistent change) of BMPR2 signalling on postnatal exposure to hyperoxia and mechanical ventilation, aggravated by prenatal cigarette smoke in a preclinical mouse model and (3) a link to defective alveolar septation and matrix remodelling through platelet derived growth factor-receptor alpha deficiency. In a treatment approach, we partially reversed vascular pathology by BMPR2-targeted treatment with FK506 in vitro and in vivo.

CONCLUSION

We identified impaired BMP signalling as a hallmark of early vascular disease in the injured neonatal lung while outlining its promising potential as a future biomarker or therapeutic target in this growing, high-risk patient population.

Insights on the bacterial composition of Parmigiano Reggiano Natural Whey Starter by a culture-dependent and 16S rRNA metabarcoding portrait

Natural whey starters (NWS) are undefined bacterial communities produced daily from whey of the previous cheese-making round, by application of high temperature. As a result, in any dairy plant, NWS are continuously evolving, undefined mixtures of several strains and/or species of lactic acid bacteria, whose composition and performance strongly depend on the selective pressure acting during incubation. While NWS is critical to assure consistency to cheese-making process, little is known about the composition, functional features, and plant-to-plant fluctuations. Here, we integrated 16S rRNA metabarcoding and culture-dependent methods to profile bacterial communities of 10 NWS sampled in the production area of Parmigiano Reggiano cheese. 16S rRNA metabarcoding analysis revealed two main NWS community types, namely NWS type-H and NWS type-D. Lactobacillus helveticus was more abundant in NWS type-H, whilst Lactobacillus delbrueckii/St. thermophilus in NWS type-D, respectively. Based on the prediction of metagenome functions, NWS type-H samples were enriched in functional pathways related to galactose catabolism and purine metabolism, while NWS type-D in pathways related to aromatic and branched chain amino acid biosynthesis, which are flavor compound precursors. Culture-dependent approaches revealed low cultivability of individual colonies as axenic cultures and high genetic diversity in the pool of cultivable survivors. Co-culturing experiments showed that fermentative performance decreases by reducing the bacterial complexity of inoculum, suggesting that biotic interactions and cross-feeding relationships could take place in NWS communities, assuring phenotypic robustness. Even though our data cannot directly predict these ecological interactions, this study provides the basis for experiments targeted at understanding how selective regime affects composition, bacterial interaction, and fermentative performance in NWS.

Extensive diversity and rapid turnover of phage defense repertoires in cheese-associated bacterial communities

BACKGROUND

Phages are key drivers of genomic diversity in bacterial populations as they impose strong selective pressure on the evolution of bacterial defense mechanisms across closely related strains. The pan-immunity model suggests that such diversity is maintained because the effective immune system of a bacterial species is the one distributed across all strains present in the community. However, only few studies have analyzed the distribution of bacterial defense systems at the community-level, mostly focusing on CRISPR and comparing samples from complex environments. Here, we studied 2778 bacterial genomes and 188 metagenomes from cheese-associated communities, which are dominated by a few bacterial taxa and occur in relatively stable environments.

RESULTS

We corroborate previous laboratory findings that in cheese-associated communities nearly identical strains contain diverse and highly variable arsenals of innate and adaptive (i.e., CRISPR-Cas) immunity systems suggesting rapid turnover. CRISPR spacer abundance correlated with the abundance of matching target sequences across the metagenomes providing evidence that the identified defense repertoires are functional and under selection. While these characteristics align with the pan-immunity model, the detected CRISPR spacers only covered a subset of the phages previously identified in cheese, providing evidence that CRISPR does not enable complete immunity against all phages, and that the innate immune mechanisms may have complementary roles.

CONCLUSIONS

Our findings show that the evolution of bacterial defense mechanisms is a highly dynamic process and highlight that experimentally tractable, low complexity communities such as those found in cheese, can help to understand ecological and molecular processes underlying phage-defense system relationships. These findings can have implications for the design of robust synthetic communities used in biotechnology and the food industry. Video Abstract.

Moral status of the fetus and the permissibility of abortion: a contractarian response to Thomson's violinist thought experiment

Judith Jarvis Thomson famously argued that abortion is permissible even if we accept that a fetus qualifies as a person and possesses a right to life. The current paper presents two arguments that undermine Thomson's position. First, the paper sketches a contractarian argument that explores Thomson's violinist thought experiment from behind a veil of ignorance, which suggests that if we had an equal likelihood of being an unwanted fetus and a pregnant woman, it would be rational for us to oppose abortion. Second, the paper discusses the hypothetical self-aborting fetus, a thought experiment that reverses the dependence relationship between a woman and a fetus. It is argued that in this scenario, where fetuses have agency of their own, Thomson's position would counterintuitively prohibit a woman from temporarily curtailing the freedom of her fetus even to save her own life.

Comparison of the Microbiome of Artisanal Homemade and Industrial Feta Cheese through Amplicon Sequencing and Shotgun Metagenomics

Feta is the most renowned protected designation of origin (PDO) white brined cheese produced in Greece. The fine organoleptic characteristics and the quality of Feta rely on, among other factors, its overall microbial ecosystem. In this study, we employed 16S rDNA and internal transcribed spacer (ITS) amplicon sequencing, as well as shotgun metagenomics, to investigate the microbiome of artisanal homemade and industrial Feta cheese samples from different regions of Greece, which has very rarely been investigated. 16S rDNA data suggested the prevalence of the Lactococcus genus in the homemade samples, while Streptococcus and Lactobacillus genera prevailed in the industrial control samples. Species identification deriving from shotgun metagenomics corroborated these findings, as Lactococcus lactis dominated two homemade samples while Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus were found to be dominating one industrial sample. ITS data revealed a complex diversity of the yeast population among the samples analyzed. Debaryomyces, Kluyveromyces, Cutaneotrichosporon, Pichia, Candida, and Rhodotorula were the major genera identified, which were distributed in a rather arbitrary manner among the different samples. Furthermore, a number of potential metagenome-assembled genomes (MAGs) could be detected among assembled shotgun bins. The overall analysis of the shotgun metagenomics supported the presence of different foodborne pathogens in homemade samples (e.g., Staphylococcus aureus, Listeria monocytogenes, Enterobacter cloacae, and Streptococcus suis), but with low to very low abundances. Concluding, the combination of both amplicon sequencing and shotgun metagenomics allowed us to obtain an in-depth profile of the artisanal homemade Feta cheese microbiome.

What influences the implementation and sustainability of antibiotic stewardship programmes in hospitals? A qualitative study of antibiotic pharmacists' perspectives across South West England

OBJECTIVES

Antibiotic stewardship programmes (ASPs) are needed at every hospital as they can improve antibiotic use and address antibiotic resistance. Pharmacists are key agents and specialists in these programmes. This study explored antibiotic pharmacists' perceptions of factors that influence the implementation and sustainability of hospital-based ASPs.

METHODS

Semistructured interviews were conducted with hospital antibiotic pharmacists face-to-face or by telephone. NVivo V.12 software was used to collate and organise the data grouped within codes. Thematic analysis was undertaken using inductive and deductive approaches to produce overarching themes.

RESULTS

Thirteen pharmacists from 13 hospitals were interviewed. Four main themes were identified: (1) 'organisational culture' which highlighted the importance of strong local clinical leadership to help achieve organisational buy-in and address resistance among physicians or clinical hierarchies; (2) 'national influences' including networks, guidance and incentive schemes which were considered to be a driver to bring about changes across organisation; (3) 'continuous monitoring with feedback ASP data, preferably through direct communication' to demonstrate the impact of the programmes which then facilitated ongoing support from local leadership and improved engagement across organisation; and (4) 'resources' which indicated the need of information technology and dedicated personnel with protected time to support ASP activities.

CONCLUSIONS

Interventions and strategies should operate at different levels-individual, team, organisational and national-to help implement and sustain ASPs in hospital. This is also the first study to identify and highlight the importance of national initiatives in contributing to the implementation and sustainability of hospital-based ASPs.

High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

Background

Next-generation sequencing (NGS) methods and especially 16S rRNA gene amplicon sequencing have become indispensable tools in microbial ecology. While they have opened up new possibilities for studying microbial communities, they also have one drawback, namely providing only relative abundances and thus compositional data. Quantitative PCR (qPCR) has been used for years for the quantification of bacteria. However, this method requires the development of specific primers and has a low throughput. The constraint of low throughput has recently been overcome by the development of high-throughput qPCR (HT-qPCR), which allows for the simultaneous detection of the most prevalent bacteria in moderately complex systems, such as cheese and other fermented dairy foods. In the present study, the performance of the two approaches, NGS and HT-qPCR, was compared by analyzing the same DNA samples from 21 Raclette du Valais protected designation of origin (PDO) cheeses. Based on the results obtained, the differences, accuracy, and usefulness of the two approaches were studied in detail.

Results

The results obtained using NGS (non-targeted) and HT-qPCR (targeted) show considerable agreement in determining the microbial composition of the cheese DNA samples studied, albeit the fundamentally different nature of these two approaches. A few inconsistencies in species detection were observed, particularly for less abundant ones. The detailed comparison of the results for 15 bacterial species/groups measured by both methods revealed a considerable bias for certain bacterial species in the measurements of the amplicon sequencing approach. We identified as probable origin to this PCR bias due to primer mismatches, variations in the number of copies for the 16S rRNA gene, and bias introduced in the bioinformatics analysis.

Conclusion

As the normalized microbial composition results of NGS and HT-qPCR agreed for most of the 21 cheese samples analyzed, both methods can be considered as complementary and reliable for studying the microbial composition of cheese. Their combined application proved to be very helpful in identifying potential biases and overcoming methodological limitations in the quantitative analysis of the cheese microbiota.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02451-y.

Assessment of the microbiological origin of blowing defects in Grana Padano Protected Designation of Origin cheese

Recognized worldwide for its history, flavor, and high nutritional quality, Grana Padano (GP) is one of the most traditional Italian raw-milk, hard-cooked, long-ripened cheese. Throughout GP manufacturing, some well-known and undesired bacterial species, such as clostridia, can proliferate and lead to spoilage defects that mischaracterize the final product; however, little is known about the development of late-blowing defects in hard cheese samples without clostridia. Therefore, in this study we aimed to use metataxonomic analysis to identify bacterial taxa associated with the development of late-blowing defect in GP samples. Furthermore, the presence of several heterofermentative lactobacilli species in defective zones were verified by primer-specific PCR assay. Considering α- and β-diversity analyses, no statistically significant differences were detected between cheese samples with and without blowing defect. Following taxonomic assignment, Lactobacillus and Streptococcus were the dominant genera, whereas clostridia-related taxa were not detected in any of the 20 analyzed samples. Using EdgeR, the genera Propionibacterium and Acinetobacter were found to be prevalently more abundant in samples categorized as having "big regular holes." In samples with "small regular holes," multiplex PCR amplification revealed differences in terms of Lactobacillus population composition, mainly obligate homofermentative lactobacilli, between defective and non-defective zones of the same cheese wheel. This study demonstrated that GP samples with blowing defects not caused by clostridial development share similar biodiversity indices with GP collected from control zones, but an imbalance of obligate homofermentative lactobacilli was noticed between samples, which requires further analysis to better comprehend the exact mechanism involved in this process.

Effectiveness of a web-based behavioural activation intervention for individuals with depression based on the Health Action Process Approach: protocol for a randomised controlled trial with a 6-month follow-up

INTRODUCTION

Behavioural activation is a highly effective treatment for depression. However, there is considerable heterogeneity of interventions grouped under the term 'behavioural activation'. A main reason for the heterogeneity is the lack of a unified theory in the intervention development: few of the established intervention manuals give a theoretical rationale for their intervention techniques. For the first time, this study will examine the effectiveness of a theory-based behavioural activation intervention (InterAKTIV) based on the Health Action Process Approach. The intervention is implemented online to ensure broad dissemination and standardisation.

METHODS AND ANALYSIS

In a two-arm randomised controlled trial, the effectiveness of a guided web-based behavioural activation intervention for people with depression will be evaluated. Participants are recruited via the print and online media of a large German healthcare insurance company. Individuals (age 18-65), who meet criteria for major depressive episode in a clinical interview and no exclusion criteria are eligible for inclusion. A target sample of 128 participants is randomly allocated to either the intervention group (immediate access to InterAKTIV) or treatment as usual (access after follow-up assessment). The primary outcome of depressive symptom severity (Quick Inventory of Depressive Symptomatology Clinician Rating) and secondary outcomes, including behavioural activation, physical activity and motivational and volitional outcomes are assessed at baseline, post treatment and 6-month follow-up. Data will be analysed on an intention-to-treat basis with additional per-protocol analyses.

ETHICS AND DISSEMINATION

This trial is approved by the ethics committee of the Albert-Ludwigs-University of Freiburg (no.: 20-1045). All participants are required to submit their informed consent online before study inclusion. The results will be submitted for publication in a peer-reviewed journal and presented at conferences.

TRIAL REGISTRATION NUMBER

This trial was registered in the German Clinical Trials Register (DRKS): DRKS00024349 (date of registration: 29 January 2021).

Omics Approaches to Assess Flavor Development in Cheese

Cheese is characterized by a rich and complex microbiota that plays a vital role during both production and ripening, contributing significantly to the safety, quality, and sensory characteristics of the final product. In this context, it is vital to explore the microbiota composition and understand its dynamics and evolution during cheese manufacturing and ripening. Application of high-throughput DNA sequencing technologies have facilitated the more accurate identification of the cheese microbiome, detailed study of its potential functionality, and its contribution to the development of specific organoleptic properties. These technologies include amplicon sequencing, whole-metagenome shotgun sequencing, metatranscriptomics, and, most recently, metabolomics. In recent years, however, the application of multiple meta-omics approaches along with data integration analysis, which was enabled by advanced computational and bioinformatics tools, paved the way to better comprehension of the cheese ripening process, revealing significant associations between the cheese microbiota and metabolites, as well as their impact on cheese flavor and quality.

The Microbiota of Grana Padano Cheese. A Review

Grana Padano (GP) is the most appreciated and marketed cheese with Protected Designation of Origin in the world. The use of raw milk, the addition of undefined cultures (defined as 'sieroinnesto naturale'), the peculiar manufacturing proces, and the long ripening make the cheese microbiota play a decisive role in defining the quality and the organoleptic properties of the product. The knowledge on the microbial diversity associated with GP has been the subject, in recent years, of several studies aimed at understanding its composition and characteristics in order, on the one hand, to improve its technological performances and, on the other hand, to indirectly enhance the nutritional quality of the product. This review aims to briefly illustrate the main available knowledge on the composition and properties of the GP microbiota, inferred from dozens of studies carried out by both classical microbiology techniques and metagenomic analysis. The paper will essentially, but not exclusively, be focused on the lactic acid bacteria (LAB) derived from starter (SLAB) and the non-starter bacteria, both lactic (NSLAB) and non-lactic, of milk origin.

Evaluation of Age-Dependent Immune Signatures in Patients With Multiple Sclerosis

BACKGROUND AND OBJECTIVES

In MS, an age-related decline in disease activity and a decreased efficacy of disease-modifying treatment have been linked to immunosenescence, a state of cellular dysfunction associated with chronic inflammation.

METHODS

To evaluate age-related immunologic alterations in MS, we compared immune signatures in peripheral blood (PB) and CSF by flow cytometry in patients with relapsing-remitting (RR) (PB n = 38; CSF n = 51) and primary progressive (PP) MS (PB n = 40; CSF n = 36) and respective controls (PB n = 40; CSF n = 85).

RESULTS

Analysis revealed significant age-related changes in blood immune cell composition, especially in the CD8 T-cell compartment of healthy donors (HDs) and patients with MS. However, HDs displayed a strong age-dependent decline in the expression of the immunoregulatory molecules KLRG1, LAG3, and CTLA-4 on memory CD8 T cells, whereas this age-dependent reduction was completely abrogated in patients with MS. An age-dependent increase in the expression of the costimulatory molecule CD226 on memory CD8 T cells was absent in patients with MS. CD226 expression correlated with disability in younger (≤50 years) patients with MS. CSF analysis revealed a significant age-dependent decline in various immune cell populations in PPMS but not RRMS, suggesting a differential effect of aging on the intrathecal compartment in PPMS.

DISCUSSION

Our data illustrate that aging in MS is associated with a dysbalance between costimulatory and immunoregulatory signals provided by CD8 T cells favoring a proinflammatory phenotype and, more importantly, a pattern of premature immune aging in the CD8 T-cell compartment of young patients with MS with potential implications for disease severity.

Cancer symptom experience and help-seeking behaviour during the COVID-19 pandemic in the UK: a cross-sectional population survey

OBJECTIVES

To understand self-reported potential cancer symptom help-seeking behaviours and attitudes during the first 6 months (March-August 2020) of the UK COVID-19 pandemic.

DESIGN

UK population-based survey conducted during August and September 2020. Correlates of help-seeking behaviour were modelled using logistic regression in participants reporting potential cancer symptoms during the previous 6 months. Qualitative telephone interviews with a purposeful subsample of participants, analysed thematically.

SETTING

Online UK wide survey.

PARTICIPANTS

7543 adults recruited via Cancer Research UK online panel provider (Dynata) and HealthWise Wales (a national register of 'research ready' participants) supplemented with social media (Facebook and Twitter) recruitment. 30 participants were also interviewed.

MAIN OUTCOME MEASURES

Survey measures included experiences of 15 potential cancer symptoms, help-seeking behaviour, barriers and prompts to help-seeking.

RESULTS

Of 3025 (40.1%) participants who experienced a potential cancer symptom, 44.8% (1355/3025) had not contacted their general practitioner (GP). Odds of help-seeking were higher among participants with disability (adjusted OR (aOR)=1.38, 95% CI 1.11 to 1.71) and who experienced more symptoms (aOR=1.68, 95% CI 1.56 to 1.82), and lower among those who perceived COVID-19 as the cause of symptom(s) (aOR=0.36, 95% CI 0.25 to 0.52). Barriers included worries about wasting the doctor's time (1158/7543, 15.4%), putting strain on healthcare services (945, 12.6%) and not wanting to make a fuss (907, 12.0%). Interviewees reported reluctance to contact the GP due to concerns about COVID-19 and fear of attending hospitals, and described putting their health concerns on hold.

CONCLUSIONS

Many people avoided healthcare services despite experiencing potential cancer symptoms during the COVID-19 pandemic. Alongside current help-seeking campaigns, well-timed and appropriate nationally coordinated campaigns should signal that services are open safely for those with unusual or persistent symptoms.

TRIAL REGISTRATION NUMBER

ISRCTN17782018.