Persistent Dysbiosis, Parasite Rise and Growth Impairment in Aquacultured European Seabass after Oxytetracycline Treatment.

The use of antibiotics in open-water aquaculture is often unavoidable when faced with pathogens with high mortality rates. In addition, seasonal pathogen surges have become more common and more intense over the years. Apart from the apparent cost of antibiotic treatment, it has been observed that, in aquaculture practice, the surviving fish often display measurable growth impairment. To understand the role of gut microbiota on the observed growth impairment, in this study, we follow the incidence of Photobacterium damselae subsp. piscicida in a seabass commercial open-water aquaculture setting in Galaxidi (Greece). Fish around 10 months of age were fed with feed containing oxytetracycline (120 mg/kg/day) for twelve days, followed by a twelve-day withdrawal period, and another eighteen days of treatment. The fish were sampled 19 days before the start of the first treatment and one month after the end of the second treatment cycle. Sequencing of the 16S rRNA gene was used to measure changes in the gut microbiome. Overall, the gut microbiota community, even a month after treatment, was highly dysbiotic and characterized by very low alpha diversity. High abundances of alkalophilic bacteria in the post-antibiotic-treated fish indicated a rise in pH that was coupled with a significant increase in gut parasites. This study's results indicate that oxytetracycline (OTC) treatment causes persistent dysbiosis even one month after withdrawal and provides a more suitable environment for an increase in parasites. These findings highlight the need for interventions to restore a healthy and protective gut microbiome.

Use of an Innovative Silage of Agro-Industrial Waste By-Products in Pig Nutrition: A Pilot Study of Its Effects on the Pig Gastrointestinal Microbiota.

The aim of this study was to evaluate whether dietary supplementation with an innovative silage (IS) created using 60% olive mill waste, 20% grape pomace, and 20% deproteinised feta cheese waste solids can modulate the composition of the intestinal microbiota in weaned (Exp. 1) and finishing (Exp. 2) pigs. In Exp. 1 (40 day supplementation), forty-five crossbred weaned pigs were randomly assigned to the 0% (Control), 5%, or 10% IS groups (15 replicates/experimental diet). In Exp. 2 (60 day supplementation), eighteen finishing pigs from Exp. 1 were fed the control diet for 8 weeks before being re-assigned to their original experimental groups and fed with the 0% (Control), 5%, or 10% IS diets (six replicates/experimental diet). Performance parameters were recorded. Ileal and caecal digesta and mucosa were collected at the end of each experiment for microbiota analysis using 16S rRNA gene sequencing (five pigs/experimental diet for Exp. 1 and six pigs/experimental diet for Exp. 2). No significant effects on pig growth parameters were observed in both experiments. In Exp. 1, 5% IS supplementation increased the relative abundance of the Prevotellaceae family, Coprococcus genus, and Alloprevotella rava (OTU_48) and reduced the relative abundance of Lactobacillus genus in the caecum compared to the control and/or 10% IS diets (p < 0.05). In Exp. 2, 5% IS supplementation led to compositionally more diverse and different ileal and caecal microbiota compared to the control group (p < 0.05; p = 0.066 for ß-diversity in ileum). Supplementation with the 5% IS increased the relative abundance of Clostridium celatum/disporicum/saudiense (OTU_3) in the ileum and caecum and Bifidobacterium pseudolongum (OTU_17) in the caecum and reduced the relative abundance of Streptococcus gallolyticus/alactolyticus (OTU_2) in the caecum compared to the control diet (p < 0.05). Similar effects on C. celatum/disporicum/saudiense and S. gallolyticus/alactolyticus were observed with the 10% IS diet in the caecum (p < 0.05). IS has the potential to beneficially alter the composition of the gastrointestinal microbiota in pigs.

Large-Scale Integration of Amplicon Data Reveals Massive Diversity within Saprospirales, Mostly Originating from Saline Environments.

The order Saprospirales, a group of bacteria involved in complex degradation pathways, comprises three officially described families: Saprospiraceae, Lewinellaceae, and Haliscomenobacteraceae. These collectively contain 17 genera and 31 species. The current knowledge on Saprospirales diversity is the product of traditional isolation methods, with the inherited limitations of culture-based approaches. This study utilized the extensive information available in public sequence repositories combined with recent analytical tools to evaluate the global evidence-based diversity of the Saprospirales order. Our analysis resulted in 1183 novel molecular families, 15,033 novel molecular genera, and 188 K novel molecular species. Of those, 7 novel families, 464 novel genera, and 1565 species appeared in abundances at ≥0.1%. Saprospirales were detected in various environments, such as saline water, freshwater, soil, various hosts, wastewater treatment plants, and other bioreactors. Overall, saline water was the environment showing the highest prevalence of Saprospirales, with bioreactors and wastewater treatment plants being the environments where they occurred with the highest abundance. Lewinellaceae was the family containing the majority of the most prevalent species detected, while Saprospiraceae was the family with the majority of the most abundant species found. This analysis should prime researchers to further explore, in a more targeted way, the Saprospirales proportion of microbial dark matter.

Darier's disease exhibits a unique cutaneous microbial dysbiosis associated with inflammation and body malodour.

BACKGROUND: Darier's disease (DD) is a genodermatosis caused by mutations of the ATP2A2 gene leading to disrupted keratinocyte adhesion. Recurrent episodes of skin inflammation and infections with a typical malodour in DD indicate a role for microbial dysbiosis. Here, for the first time, we investigated the DD skin microbiome using a metabarcoding approach of 115 skin swabs from 14 patients and 14 healthy volunteers. Furthermore, we analyzed its changes in the context of DD malodour and the cutaneous DD transcriptome. RESULTS: We identified a disease-specific cutaneous microbiome with a loss of microbial diversity and of potentially beneficial commensals. Expansion of inflammation-associated microbes such as Staphylococcus aureus and Staphylococcus warneri strongly correlated with disease severity. DD dysbiosis was further characterized by abundant species belonging to Corynebacteria, Staphylococci and Streptococci groups displaying strong associations with malodour intensity. Transcriptome analyses showed marked upregulation of epidermal repair, inflammatory and immune defence pathways reflecting epithelial and immune response mechanisms to DD dysbiotic microbiome. In contrast, barrier genes including claudin-4 and cadherin-4 were downregulated. CONCLUSIONS: These findings allow a better understanding of Darier exacerbations, highlighting the role of cutaneous dysbiosis in DD inflammation and associated malodour. Our data also suggest potential biomarkers and targets of intervention for DD. Video Abstract.

Early life gut microbiota profiles linked to synbiotic formula effects: a randomized clinical trial in European infants.

BACKGROUND: Microbial colonization of the gastrointestinal tract after birth is an essential event that influences infant health with life-long consequences. Therefore, it is important to investigate strategies to positively modulate colonization in early life. OBJECTIVES: This randomized, controlled intervention study included 540 infants to investigate the effects of a synbiotic intervention formula (IF) containing Limosilactobacillus fermentum CECT5716 and galacto-oligosaccharides on the fecal microbiome. METHODS: The fecal microbiota from infants was analyzed by 16S rRNA amplicon sequencing at 4, 12, and 24 months of age. Metabolites (e.g., short-chain fatty acids) and other milieu parameters (e.g., pH, humidity, and IgA) were also measured in stool samples. RESULTS: Microbiota profiles changed with age, with major differences in diversity and composition. Significant effects of the synbiotic IF compared with control formula (CF) were visible at month 4, including higher occurrence of Bifidobacterium spp. and Lactobacillaceae and lower occurrence of Blautia spp., as well as Ruminoccocus gnavus and relatives. This was accompanied by lower fecal pH and concentrations of butyrate. After de novo clustering at 4 months of age, overall phylogenetic profiles of the infants receiving IF were closer to reference profiles of those fed with human milk than infants fed CF. The changes owing to IF were associated with fecal microbiota states characterized by lower occurrence of Bacteroides compared with higher levels of Firmicutes (valid name Bacillota), Proteobacteria (valid name Pseudomonadota), and Bifidobacterium at 4 months of age. These microbiota states were linked to higher prevalence of infants born by Cesarean section. CONCLUSIONS: The synbiotic intervention influenced fecal microbiota and milieu parameters at an early age depending on the overall microbiota profiles of the infants, sharing a few similarities with breastfed infants. This trial was registered at clinicaltrials.gov as NCT02221687.

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.

The Development of the Bacterial Community of Brown Trout (Salmo trutta) during Ontogeny.

Brown trout (Salmo trutta) is an important aquaculture species in Germany, but its production faces challenges due to global warming and a high embryo mortality. Climate factors might influence the fish's bacterial community (BC) and thus increase embryo mortality. Yet, knowledge of the physiological BC during ontogeny in general is scarce. In this project, the BC of brown trout has been investigated in a period from unfertilized egg to 95 days post fertilization (dpf) using 16S rRNA gene amplicon sequencing. Developmental changes differed between early and late ontogeny and major differences in BC occurred especially during early developmental stages. Thus, analysis was conducted separately for 0 to 67 dpf and from 67 to 95 dpf. All analyzed stages were sampled in toto to avoid bias due to different sampling methods in different developmental stages. The most abundant phylum in the BC of all developmental stages was Pseudomonadota, while only two families (Comamonadaceae and Moraxellaceae) occurred in all developmental stages. The early developmental stages until 67 dpf displayed greater shifts in their BC regarding bacterial richness, microbial diversity, and taxonomic composition. Thereafter, in the fry stages, the BC seemed to stabilize and changes were moderate. In future studies, a reduction in the sampling time frames during early development, an increase in sampling numbers, and an attempt for biological reproduction in order to characterize the causes of these variations is recommended.

Cronos: A Machine Learning Pipeline for Description and Predictive Modeling of Microbial Communities Over Time.

Microbial time-series analysis, typically, examines the abundances of individual taxa over time and attempts to assign etiology to observed patterns. This approach assumes homogeneous groups in terms of profiles and response to external effectors. These assumptions are not always fulfilled, especially in complex natural systems, like the microbiome of the human gut. It is actually established that humans with otherwise the same demographic or dietary backgrounds can have distinct microbial profiles. We suggest an alternative approach to the analysis of microbial time-series, based on the following premises: 1) microbial communities are organized in distinct clusters of similar composition at any time point, 2) these intrinsic subsets of communities could have different responses to the same external effects, and 3) the fate of the communities is largely deterministic given the same external conditions. Therefore, tracking the transition of communities, rather than individual taxa, across these states, can enhance our understanding of the ecological processes and allow the prediction of future states, by incorporating applied effects. We implement these ideas into Cronos, an analytical pipeline written in R. Cronos' inputs are a microbial composition table (e.g., OTU table), their phylogenetic relations as a tree, and the associated metadata. Cronos detects the intrinsic microbial profile clusters on all time points, describes them in terms of composition, and records the transitions between them. Cluster assignments, combined with the provided metadata, are used to model the transitions and predict samples' fate under various effects. We applied Cronos to available data from growing infants' gut microbiomes, and we observe two distinct trajectories corresponding to breastfed and formula-fed infants that eventually converge to profiles resembling those of mature individuals. Cronos is freely available at https://github.com/Lagkouvardos/Cronos.

Taxonomy Informed Clustering, an Optimized Method for Purer and More Informative Clusters in Diversity Analysis and Microbiome Profiling.

Bacterial diversity is often analyzed using 16S rRNA gene amplicon sequencing. Commonly, sequences are clustered based on similarity cutoffs to obtain groups reflecting molecular species, genera, or families. Due to the amount of the generated sequencing data, greedy algorithms are preferred for their time efficiency. Such algorithms rely only on pairwise sequence similarities. Thus, sometimes sequences with diverse phylogenetic background are clustered together. In contrast, taxonomic classifiers use position specific taxonomic information in assigning a probable taxonomy to a given sequence. Here we introduce Taxonomy Informed Clustering (TIC), a novel approach that utilizes classifier-assigned taxonomy to restrict clustering to only those sequences that share the same taxonomic path. Based on this concept, we offer a complete and automated pipeline for processing of 16S rRNA amplicon datasets in diversity analyses. First, raw reads are processed to form denoised amplicons. Next, the denoised amplicons are taxonomically classified. Finally, the TIC algorithm progressively assigning clusters at molecular species, genus and family levels. TIC outperforms greedy clustering algorithms like USEARCH and VSEARCH in terms of clusters' purity and entropy, when using data from the Living Tree Project as test samples. Furthermore, we applied TIC on a dataset containing all Bifidobacteriaceae-classified sequences from the IMNGS database. Here, TIC identified evidence for 1000s of novel molecular genera and species. These results highlight the straightforward application of the TIC pipeline and superior results compared to former methods in diversity studies. The pipeline is freely available at: https://github.com/Lagkouvardos/TIC.

DivCom: A Tool for Systematic Partition of Groups of Microbial Profiles Into Intrinsic Subclusters and Distance-Based Subgroup Comparisons.

When analyzing microbiome data, one of the main objectives is to effectively compare the microbial profiles of samples belonging to different groups. Beta diversity measures the level of similarity among samples, usually in the form of dissimilarity matrices. The use of suitable statistical tests in conjunction with those matrices typically provides us with all the necessary information to evaluate the overall similarity of groups of microbial communities. However, in some cases, this approach can lead us to deceptive conclusions, mainly due to the uneven dispersions of the groups and the existence of unique or unexpected substructures in the dataset. To address these issues, we developed divide and compare (DivCom), an automated tool for advanced beta diversity analysis. DivCom reveals the inner structure of groups by dividing their samples into the appropriate number of clusters and then compares the distances of every profile to the centers of these clusters. This information can be used for determining the existing interrelation of the groups. The proposed methodology and the developed tool were assessed by comparing the response of anemic patients with or without inflammatory bowel disease to different iron replacement therapies. DivCom generated results that revealed the inner structure of the dataset, evaluated the relationship among the clusters, and assessed the effect of the treatments. The DivCom tool is freely available at: https://github.com/Lagkouvardos/DivCom.

Namco: a microbiome explorer.

16S rRNA gene profiling is currently the most widely used technique in microbiome research and allows the study of microbial diversity, taxonomic profiling, phylogenetics, functional and network analysis. While a plethora of tools have been developed for the analysis of 16S rRNA gene data, only a few platforms offer a user-friendly interface and none comprehensively covers the whole analysis pipeline from raw data processing down to complex analysis. We introduce Namco, an R shiny application that offers a streamlined interface and serves as a one-stop solution for microbiome analysis. We demonstrate Namco's capabilities by studying the association between a rich fibre diet and the gut microbiota composition. Namco helped to prove the hypothesis that butyrate-producing bacteria are prompted by fibre-enriched intervention. Namco provides a broad range of features from raw data processing and basic statistics down to machine learning and network analysis, thus covering complex data analysis tasks that are not comprehensively covered elsewhere. Namco is freely available at https://exbio.wzw.tum.de/namco/.

The "Crosstalk" between Microbiota and Metabolomic Profile of Kefalograviera Cheese after the Innovative Feeding Strategy of Dairy Sheep by Omega-3 Fatty Acids.

The purpose of this study was to examine the effects of two different feeding systems, a control or a flaxseed and lupin diet (experimental), for a sheep flock, on the microbiota and metabolome of Kefalograviera cheese samples produced by their milk. In particular, the microbiota present in Kefalograviera cheese samples was analyzed using 16S rRNA gene sequencing, while ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to investigate the chemical profile of the cheeses, considering the different feeding systems applied. The metagenomic profile was found to be altered by the experimental feeding system and significantly correlated to specific cheese metabolites, with Streptococcaceae and Lactobacillaceae establishing positive and negative correlations with the discriminant metabolites. Overall, more than 120 features were annotated and identified with high confidence level across the samples while most of them belonged to specific chemical classes. Characteristic analytes detected in different concentrations in the experimental cheese samples including arabinose, dulcitol, hypoxanthine, itaconic acid, L-arginine, L-glutamine and succinic acid. Therefore, taken together, our results provide an extensive foodomics approach for Kefalograviera cheese samples from different feeding regimes, investigating the metabolomic and metagenomic biomarkers that could be used to foresee, improve, and control cheese ripening outcomes, demonstrating the quality of the experimental Kefalograviera cheese.

Alteration of Intestinal Microbiome of Clostridioides difficile-Infected Hamsters during the Treatment with Specific Cow Antibodies.

Clostridioides difficile infection (CDI) often develops after pretreatment with antibiotics, which can lead to damage of the intestinal microbiome. The approach of this study was to use specific polyclonal antibodies isolated from the milk of immunized cows to treat CDI, in contrast to the standard application of nonspecific antibiotics. To gain a deeper understanding of the role of the microbiome in the treatment of CDI with bovine antibodies, stool and intestinal fluid samples of hamsters were collected in large quantities from various treatments (>400 samples). The results show that the regeneration of the microbiome instantly begins with the start of the antibody treatment, in contrast to the Vancomycin-treated group where the diversity decreased significantly during the treatment duration. All antibody-treated hamsters that survived the initial phase also survived the entire study period. The results also show that the regeneration of the microbiome was not an antibody-induced regeneration, but a natural regeneration that occurred because no microbiota-inactivating substances were administered. In conclusion, the treatment with bovine antibodies is a functional therapy for both the acute treatment and the prevention of recurrence in hamsters and could meet the urgent need for CDI treatment alternatives in humans.

MiMiC: a bioinformatic approach for generation of synthetic communities from metagenomes.

Environmental and host-associated microbial communities are complex ecosystems, of which many members are still unknown. Hence, it is challenging to study community dynamics and important to create model systems of reduced complexity that mimic major community functions. Therefore, we developed MiMiC, a computational approach for data-driven design of simplified communities from shotgun metagenomes. We first built a comprehensive database of species-level bacterial and archaeal genomes (n = 22 627) consisting of binary (presence/absence) vectors of protein families (Pfam = 17 929). MiMiC predicts the composition of minimal consortia using an iterative scoring system based on maximal match-to-mismatch ratios between this database and the Pfam binary vector of any input metagenome. Pfam vectorization retained enough resolution to distinguish metagenomic profiles between six environmental and host-derived microbial communities (n = 937). The calculated number of species per minimal community ranged between 5 and 11, with MiMiC selected communities better recapitulating the functional repertoire of the original samples than randomly selected species. The inferred minimal communities retained habitat-specific features and were substantially different from communities consisting of most abundant members. The use of a mixture of known microbes revealed the ability to select 23 of 25 target species from the entire genome database. MiMiC is open source and available at https://github.com/ClavelLab/MiMiC.

Pre-digest of unprotected DNA by Benzonase improves the representation of living skin bacteria and efficiently depletes host DNA.

BACKGROUND: The identification of microbiota based on next-generation sequencing (NGS) of extracted DNA has drastically improved our understanding of the role of microbial communities in health and disease. However, DNA-based microbiome analysis cannot per se differentiate between living and dead microorganisms. In environments such as the skin, host defense mechanisms including antimicrobial peptides and low cutaneous pH result in a high microbial turnover, likely resulting in high numbers of dead cells present and releasing substantial amounts of microbial DNA. NGS analyses may thus lead to inaccurate estimations of microbiome structures and consequently functional capacities. RESULTS: We investigated in this study the feasibility of a Benzonase-based approach (BDA) to pre-digest unprotected DNA, i.e., of dead microbial cells, as a method to overcome these limitations, thus offering a more accurate assessment of the living microbiome. A skin mock community as well as skin microbiome samples were analyzed using 16S rRNA gene sequencing and metagenomics sequencing after DNA extraction with and without a Benzonase digest to assess bacterial diversity patterns. The BDA method resulted in less reads from dead bacteria both in the skin mock community and skin swabs spiked with either heat-inactivated bacteria or bacterial-free DNA. This approach also efficiently depleted host DNA reads in samples with high human-to-microbial DNA ratios, with no obvious impact on the microbiome profile. We further observed that low biomass samples generate an α-diversity bias when the bacterial load is lower than 105 CFU and that Benzonase digest is not sufficient to overcome this bias. CONCLUSIONS: The BDA approach enables both a better assessment of the living microbiota and depletion of host DNA reads. Video abstract.

Endophytic Bacterial Isolates From Halophytes Demonstrate Phytopathogen Biocontrol and Plant Growth Promotion Under High Salinity.

Halophytic endophytes potentially contribute to the host's adaptation to adverse environments, improving its tolerance against various biotic and abiotic stresses. Here, we identified the culturable endophytic bacteria of three crop wild relative (CWR) halophytes: Cakile maritima, Matthiola tricuspidata, and Crithmum maritimum. In the present study, the potential of these isolates to improve crop adaptations to various stresses was investigated, using both in vitro and in-planta approaches. Endophytic isolates were identified by their 16S rRNA gene sequence and evaluated for their ability to: grow in vitro in high levels of NaCl; inhibit the growth of the economically important phytopathogens Verticillium dahliae, Ralstonia solanacearum, and Clavibacter michiganensis and the human pathogen Aspergillus fumigatus; provide salt tolerance in-planta; and provide growth promoting effect in-planta. Genomes of selected isolates were sequenced. In total, 115 endophytic isolates were identified. At least 16 isolates demonstrated growth under increased salinity, plant growth promotion and phytopathogen antagonistic activity. Three showed in-planta suppression of Verticillium growth. Furthermore, representatives of three novel species were identified: two Pseudomonas species and one Arthrobacter. This study provides proof-of-concept that the endophytes from CWR halophytes can be used as "bio-inoculants," for the enhancement of growth and stress tolerance in crops, including the high-salinity stress.

Processing Matters in Nutrient-Matched Laboratory Diets for Mice-Microbiome.

The composition of the microbiome is subject to the host's diet. In commercial laboratory mouse diets, different physical forms of the same diets are available, containing-according to their labels-identical ingredients and nutrient compositions. However, variations in nutrient composition and starch gelatinization due to production processes and their impact on digestibility have been described. In this study, a total of 48 C57BL/J6 mice were assigned to two equal groups and were fed diets (produced with different processes-extruded vs. pelleted) for eight weeks in two biological replicates. At the end of the experiment, samples were collected from five different gastrointestinal regions, including the stomach, small intestine, cecum, large intestine, and an extracorporeal region (feces), and the microbiome was analyzed with 16S rRNA gene amplicon sequencing. The replicates in both experiments differed significantly in their relative abundances of Muribaculaceae species. Furthermore, the gastrointestinal content of pellet-fed mice contained larger numbers of Lactobacillus species. These results indicate that starch gelatinization and ingredient composition significantly influence microbial makeup. In conclusion, different feed processing methods may affect fundamental digestive and metabolic processes, impacting animal experiments and biasing microbiome data.

Recent advances in culture-based gut microbiome research.

Gut microbes affect the physiology of their hosts. Studying their diversity and functions is thus of utmost importance as it will open new avenues towards the discovery of new biomolecules and the treatment of diseases. Gut microbiome research is currently boosted by the unification of metagenomics, which has dominated the field in the last two decades, and cultivation, which is experiencing a renaissance. Each of these approaches has advantages and drawbacks that can be overcome if used synergistically. In this brief article, we summarize recent literature and own studies on the cultivation of gut microbes, provide a succinct status quo of cultured fractions and collections of isolates, and give short opinions on challenges and next steps to take.