Microbial foods for improving human and planetary health.

The current food production system is negatively impacting planetary and human health. A transition to a sustainable and fair food system is urgently needed. Microorganisms are likely enablers of this process, as they can produce delicious and healthy microbial foods with low environmental footprints. We review traditional and current approaches to microbial foods, such as fermented foods, microbial biomass, and food ingredients derived from microbial fermentations. We discuss how future advances in science-driven fermentation, synthetic biology, and sustainable feedstocks enable a new generation of microbial foods, potentially impacting the sustainability, resilience, and health effects of our food system.

Pharmacogenomics of GPCR Drug Targets.

Natural genetic variation in the human genome is a cause of individual differences in responses to medications and is an underappreciated burden on public health. Although 108 G-protein-coupled receptors (GPCRs) are the targets of 475 (∼34%) Food and Drug Administration (FDA)-approved drugs and account for a global sales volume of over 180 billion US dollars annually, the prevalence of genetic variation among GPCRs targeted by drugs is unknown. By analyzing data from 68,496 individuals, we find that GPCRs targeted by drugs show genetic variation within functional regions such as drug- and effector-binding sites in the human population. We experimentally show that certain variants of µ-opioid and Cholecystokinin-A receptors could lead to altered or adverse drug response. By analyzing UK National Health Service drug prescription and sales data, we suggest that characterizing GPCR variants could increase prescription precision, improving patients' quality of life, and relieve the economic and societal burden due to variable drug responsiveness. VIDEO ABSTRACT.

Pangenome analysis reveals the genetic basis for taxonomic classification of the Lactobacillaceae family.

Lactobacillaceae represent a large family of important microbes that are foundational to the food industry. Many genome sequences of Lactobacillaceae strains are now available, enabling us to conduct a comprehensive pangenome analysis of this family. We collected 3591 high-quality genomes from public sources and found that: 1) they contained enough genomes for 26 species to perform a pangenomic analysis, 2) the normalized Heap's coefficient λ (a measure of pangenome openness) was found to have an average value of 0.27 (ranging from 0.07 to 0.37), 3) the pangenome openness was correlated with the abundance and genomic location of transposons and mobilomes, 4) the pangenome for each species was divided into core, accessory, and rare genomes, that highlight the species-specific properties (such as motility and restriction-modification systems), 5) the pangenome of Lactiplantibacillus plantarum (which contained the highest number of genomes found amongst the 26 species studied) contained nine distinct phylogroups, and 6) genome mining revealed a richness of detected biosynthetic gene clusters, with functions ranging from antimicrobial and probiotic to food preservation, but ∼93% were of unknown function. This study provides the first in-depth comparative pangenomics analysis of the Lactobacillaceae family.

Compatibility of Evolutionary Responses to Constituent Antibiotics Drive Resistance Evolution to Drug Pairs.

Antibiotic combinations are considered a relevant strategy to tackle the global antibiotic resistance crisis since they are believed to increase treatment efficacy and reduce resistance evolution (WHO treatment guidelines for drug-resistant tuberculosis: 2016 update.). However, studies of the evolution of bacterial resistance to combination therapy have focused on a limited number of drugs and have provided contradictory results (Lipsitch, Levin BR. 1997; Hegreness et al. 2008; Munck et al. 2014). To address this gap in our understanding, we performed a large-scale laboratory evolution experiment, adapting eight replicate lineages of Escherichia coli to a diverse set of 22 different antibiotics and 33 antibiotic pairs. We found that combination therapy significantly limits the evolution of de novode novo resistance in E. coli, yet different drug combinations vary substantially in their propensity to select for resistance. In contrast to current theories, the phenotypic features of drug pairs are weak predictors of resistance evolution. Instead, the resistance evolution is driven by the relationship between the evolutionary trajectories that lead to resistance to a drug combination and those that lead to resistance to the component drugs. Drug combinations requiring a novel genetic response from target bacteria compared with the individual component drugs significantly reduce resistance evolution. These data support combination therapy as a treatment option to decelerate resistance evolution and provide a novel framework for selecting optimized drug combinations based on bacterial evolutionary responses.

Reconstructing the transcriptional regulatory network of probiotic L. reuteri is enabled by transcriptomics and machine learning.

Limosilactobacillus reuteri, a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) to 117 RNA-seq data sets to decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific gene sets. Our findings indicate that the ICA provides a qualitative advancement and captures nuanced relationships within gene clusters that other methods may miss. This study uncovers the fundamental properties of L. reuteri's TRN and deepens our understanding of its arginine metabolism and the co-regulation of riboflavin metabolism and fatty acid conversion. It also sheds light on conditions that regulate genes within a specific biosynthetic gene cluster and allows for the speculation of the potential role of isoprenoid biosynthesis in L. reuteri's adaptive response to environmental changes. By integrating transcriptomics and machine learning, we provide a system-level understanding of L. reuteri's response mechanism to environmental fluctuations, thus setting the stage for modeling the probiotic transcriptome for applications in microbial food production. IMPORTANCE: We have studied Limosilactobacillus reuteri, a beneficial probiotic microbe that plays a significant role in our health and production of sustainable foods, a type of foods that are nutritionally dense and healthier and have low-carbon emissions compared to traditional foods. Similar to how humans adapt their lifestyles to different environments, this microbe adjusts its behavior by modulating the expression of genes. We applied machine learning to analyze large-scale data sets on how these genes behave across diverse conditions. From this, we identified 35 unique patterns demonstrating how L. reuteri adjusts its genes based on 50 unique environmental conditions (such as various sugars, salts, microbial cocultures, human milk, and fruit juice). This research helps us understand better how L. reuteri functions, especially in processes like breaking down certain nutrients and adapting to stressful changes. More importantly, with our findings, we become closer to using this knowledge to improve how we produce more sustainable and healthier foods with the help of microbes.

Derivation of Kokumi γ-Glutamyl Peptides and Volatile Aroma Compounds from Fermented Cereal Processing By-Products for Reducing Bitterness of Plant-Based Ingredients.

Current food production methods and consumption behaviours are unsustainable and contribute to environmental harm. One example is food waste-around 38% of food produced is wasted each year. Here, we show that two common food waste products, wheat bran and brewer's spent grain, can successfully be upcycled via miso fermentation. During the fermentation process, kokumi γ-glutamyl peptides, known to increase mouthfulness, are produced; these include γ-ECG (oxidized), γ-EVG, γ-EV, γ-EE, γ-EF, and γ-EL. The profiles of kokumi peptides and volatile aroma compounds are correlated with koji substrate, pH, and enzymatic activity, offering straightforward parameters that can be manipulated to increase the abundance of kokumi peptides during the fermentation process. Correlation analysis demonstrates that some volatile aroma compounds, such as fatty acid ethyl esters, are correlated with kokumi peptide abundance and may be responsible for fatty, greasy, and buttery aromas. Consumer sensory analysis conveys that the bitter taste of vegetables, such as that in endives, can be dampened when miso extract containing kokumi peptides is added. This suggests that kokumi peptides, along with aroma volatile compounds, can enhance the overall flavour of plant-based products. This study opens new opportunities for cereal processing by-product upcycling via fermentation, ultimately having the potential to promote a plant-based diet.

[Cross-regional telemedicine services as a supplement to rural primary care: a mixed-methods analysis]. / Überregionale telemedizinische Ergänzungsbehandlung für die ländliche Hausarztversorgung - eine Mixed-Methods-Analyse.

BACKGROUND: Family doctor care in rural areas is facing upheaval. On the one hand, demographic change is increasing patient demand, but on the other hand, it is also reducing physician density. In this context, telemedicine opens up new potentials for care. This study explores the possibilities of digitalization in family care with diverse stakeholders. The most important element of this work is to explore the attitudes towards telemedical supplementary options in primary care. In doing so, the chances and concerns of both general practitioners and citizens will be analyzed. The aim is to find out possibilities which can relieve GPs and support the health care provision in rural regions in the long term. METHODOLOGY AND MATERIAL: A mixed-methods design combines findings from qualitative semi-structured guided interviews with general practitioners (N=8) with a quantitative citizen survey (N=1,276) in a rural region. RESULTS: Concern about future health care provision is high among physicians and citizens. Although physicians see a need for action and opportunities through telemedicine measures, they also raise clear concerns about the doctor-patient relationship. The citizens are principally open to various telemedical options and can imagine using simple services such as e-prescription and e-appointment booking. DISCUSSION: These results can serve as a basis for the further development of digital offerings of family doctors' offices as well as other model projects in rural regions, if they guarantee low-threshold access, are implemented in cooperation with doctors and patients and do not endanger the established doctor-patient relationship. CONCLUSION: There are major concerns about the future of family physician care, especially in rural areas. The COVID-19 pandemic opens up opportunities for digitization across age boundaries. Initially, however, telemedicine care can only have a supplementary role. Low-threshold offerings in close cooperation with the family doctor are particularly promising here.

Bacterial resistance to CRISPR-Cas antimicrobials.

In the age of antibiotic resistance and precise microbiome engineering, CRISPR-Cas antimicrobials promise to have a substantial impact on the way we treat diseases in the future. However, the efficacy of these antimicrobials and their mechanisms of resistance remain to be elucidated. We systematically investigated how a target E. coli strain can escape killing by episomally-encoded CRISPR-Cas9 antimicrobials. Using Cas9 from Streptococcus pyogenes (SpCas9) we studied the killing efficiency and resistance mutation rate towards CRISPR-Cas9 antimicrobials and elucidated the underlying genetic alterations. We find that killing efficiency is not correlated with the number of cutting sites or the type of target. While the number of targets did not significantly affect efficiency of killing, it did reduce the emergence of chromosomal mutations conferring resistance. The most frequent target of resistance mutations was the plasmid-encoded SpCas9 that was inactivated by bacterial genome rearrangements involving translocation of mobile genetic elements such as insertion elements. This resistance mechanism can be overcome by re-introduction of an intact copy of SpCas9. The work presented here provides a guide to design strategies that reduce resistance and improve the activity of CRISPR-Cas antimicrobials.

Extraction and high-throughput sequencing of oak heartwood DNA: Assessing the feasibility of genome-wide DNA methylation profiling.

Tree ring features are affected by environmental factors and therefore are the basis for dendrochronological studies to reconstruct past environmental conditions. Oak wood often provides the data for these studies because of the durability of oak heartwood and hence the availability of samples spanning long time periods of the distant past. Wood formation is regulated in part by epigenetic mechanisms such as DNA methylation. Studies of the methylation state of DNA preserved in oak heartwood thus could identify epigenetic tree ring features informing on past environmental conditions. In this study, we aimed to establish protocols for the extraction of DNA, the high-throughput sequencing of whole-genome DNA libraries (WGS) and the profiling of DNA methylation by whole-genome bisulfite sequencing (WGBS) for oak (Quercus robur) heartwood drill cores taken from the trunks of living standing trees spanning the AD 1776-2014 time period. Heartwood contains little DNA, and large amounts of phenolic compounds known to hinder the preparation of high-throughput sequencing libraries. Whole-genome and DNA methylome library preparation and sequencing consistently failed for oak heartwood samples more than 100 and 50 years of age, respectively. DNA fragmentation increased with sample age and was exacerbated by the additional bisulfite treatment step during methylome library preparation. Relative coverage of the non-repetitive portion of the oak genome was sparse. These results suggest that quantitative methylome studies of oak hardwood will likely be limited to relatively recent samples and will require a high sequencing depth to achieve sufficient genome coverage.

Dominant resistance and negative epistasis can limit the co-selection of de novo resistance mutations and antibiotic resistance genes.

To tackle the global antibiotic resistance crisis, antibiotic resistance acquired either vertically by chromosomal mutations or horizontally through antibiotic resistance genes (ARGs) have been studied. Yet, little is known about the interactions between the two, which may impact the evolution of antibiotic resistance. Here, we develop a multiplexed barcoded approach to assess the fitness of 144 mutant-ARG combinations in Escherichia coli subjected to eight different antibiotics at 11 different concentrations. While most interactions are neutral, we identify significant interactions for 12% of the mutant-ARG combinations. The ability of most ARGs to confer high-level resistance at a low fitness cost shields the selective dynamics of mutants at low drug concentrations. Therefore, high-fitness mutants are often selected regardless of their resistance level. Finally, we identify strong negative epistasis between two unrelated resistance mechanisms: the tetA tetracycline resistance gene and loss-of-function nuo mutations involved in aminoglycoside tolerance. Our study highlights important constraints that may allow better prediction and control of antibiotic resistance evolution.

Dependency of Heterochromatin Domains on Replication Factors.

Chromatin structure regulates both genome expression and dynamics in eukaryotes, where large heterochromatic regions are epigenetically silenced through the methylation of histone H3K9, histone deacetylation, and the assembly of repressive complexes. Previous genetic screens with the fission yeast Schizosaccharomyces pombe have led to the identification of key enzymatic activities and structural constituents of heterochromatin. We report here on additional factors discovered by screening a library of deletion mutants for silencing defects at the edge of a heterochromatic domain bound by its natural boundary-the IR-R+ element-or by ectopic boundaries. We found that several components of the DNA replication progression complex (RPC), including Mrc1/Claspin, Mcl1/Ctf4, Swi1/Timeless, Swi3/Tipin, and the FACT subunit Pob3, are essential for robust heterochromatic silencing, as are the ubiquitin ligase components Pof3 and Def1, which have been implicated in the removal of stalled DNA and RNA polymerases from chromatin. Moreover, the search identified the cohesin release factor Wpl1 and the forkhead protein Fkh2, both likely to function through genome organization, the Ssz1 chaperone, the Fkbp39 proline cis-trans isomerase, which acts on histone H3P30 and P38 in Saccharomyces cerevisiae, and the chromatin remodeler Fft3. In addition to their effects in the mating-type region, to varying extents, these factors take part in heterochromatic silencing in pericentromeric regions and telomeres, revealing for many a general effect in heterochromatin. This list of factors provides precious new clues with which to study the spatiotemporal organization and dynamics of heterochromatic regions in connection with DNA replication.

Chromosomal barcoding as a tool for multiplexed phenotypic characterization of laboratory evolved lineages.

Adaptive laboratory evolution is an important tool to evolve organisms to increased tolerance towards different physical and chemical stress. It is applied to study the evolution of antibiotic resistance as well as genetic mechanisms underlying improvements in production strains. Adaptive evolution experiments can be automated in a high-throughput fashion. However, the characterization of the resulting lineages can become a time consuming task, when the performance of each lineage is evaluated individually. Here, we present a novel method for the markerless insertion of randomized genetic barcodes into the genome of Escherichia coli using a novel dual-auxotrophic selection approach. The barcoded E. coli library allows multiplexed phenotyping of evolved strains in pooled competition experiments. We use the barcoded library in an adaptive evolution experiment; evolving resistance towards three common antibiotics. Comparing this multiplexed phenotyping with conventional susceptibility testing and growth-rate measurements we can show a significant positive correlation between the two approaches. Use of barcoded bacterial strain libraries for individual adaptive evolution experiments drastically reduces the workload of characterizing the resulting phenotypes and enables prioritization of lineages for in-depth characterization. In addition, barcoded clones open up new ways to profile community dynamics or to track lineages in vivo or situ.

Adaptive Laboratory Evolution of Antibiotic Resistance Using Different Selection Regimes Lead to Similar Phenotypes and Genotypes.

Antibiotic resistance is a global threat to human health, wherefore it is crucial to study the mechanisms of antibiotic resistance as well as its emergence and dissemination. One way to analyze the acquisition of de novo mutations conferring antibiotic resistance is adaptive laboratory evolution. However, various evolution methods exist that utilize different population sizes, selection strengths, and bottlenecks. While evolution in increasing drug gradients guarantees high-level antibiotic resistance promising to identify the most potent resistance conferring mutations, other selection regimes are simpler to implement and therefore allow higher throughput. The specific regimen of adaptive evolution may have a profound impact on the adapted cell state. Indeed, substantial effects of the selection regime on the resulting geno- and phenotypes have been reported in the literature. In this study we compare the geno- and phenotypes of Escherichia coli after evolution to Amikacin, Piperacillin, and Tetracycline under four different selection regimes. Interestingly, key mutations that confer antibiotic resistance as well as phenotypic changes like collateral sensitivity and cross-resistance emerge independently of the selection regime. Yet, lineages that underwent evolution under mild selection displayed a growth advantage independently of the acquired level of antibiotic resistance compared to lineages adapted under maximal selection in a drug gradient. Our data suggests that even though different selection regimens result in subtle genotypic and phenotypic differences key adaptations appear independently of the selection regime.