Assessment of Fungal Lytic Enzymatic Extracts Produced Under Submerged Fermentation as Enhancers of Entomopathogens' Biological Activity.

The application of enzymes in agricultural fields has been little explored. One potential application of fungal lytic enzymes (chitinases, lipases, and proteases) is as an additive to current biopesticides to increase their efficacy and reduce the time of mortality. For this, a screening of lytic overproducer fungi under submerged fermentation with a chemical-defined medium was performed. Then, the enzymatic crude extract (ECE) was concentrated and partially characterized. This characterization consisted of measuring the enzymatic activity (lipase, protease and, chitinase) and determining the enzyme stability after storage at temperatures of - 80, - 20 and, 4 °C. And lastly, the application of these concentrated enzymatic crude extracts (C-ECE) as an enhancer of spores-based fungal biopesticide was proven. Beauveria were not as good producers of lytic enzymes as the strains from Trichoderma and Metarhizium. The isolate M. robertsii Mt015 was selected for the co-production of chitinases and proteases; and the isolate T. harzianum Th180 for co-production of chitinases, lipases, and proteases. The C-ECE of Mt015 had a protease activity of 18.6 ± 1.1 U ml-1, chitinase activity of 0.28 ± 0.01 U ml-1, and no lipase activity. Meanwhile, the C-ECE of Th180 reached a chitinase activity of 0.75 U ml-1, lipase activity of 0.32 U ml-1, and protease activity of 0.24 U ml-1. Finally, an enhancing effect of the enzymatic extracts of M. robertsii (66.7%) and T. harzianum (43.5%) on the efficacy of B. bassiana Bv064 against Diatraea saccharalis larvae was observed. This work demonstrates the non-species-specific enhancing effect of enzymatic extracts on the insecticidal activity of conidial-based biopesticides, which constitutes a contribution to the improvement of biological control agents' performance.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study Highlights: The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Scale-Up of Duddingtonia flagrans Chlamydospores Production from Laboratory to Pilot-Scale Using a Solid-State Fermentation System.

The fungus Duddingtonia flagrans is a biological control tool to reduce infective larvae of gastrointestinal nematode in pastures. To create a commercially available bioproduct based on a nematophagous fungus, an efficient mass production process should be developed that is able to guarantee a good predatory capacity and satisfactory production rates. In this work, solid-state fermentation (SSF) parameters were investigated to produce D. flagrans at pilot-scale. The results showed that the relative humidity was a critical factor to increase productivity and to reduce fermentation time. The best production conditions using a tray bioreactor were a relative humidity in the room at 90% for 2 days, and inoculation by sprinkling. The fermentation process was composed of 7 days under submerged fermentation to produce the inoculum and 7 more days of SSF in a tray bioreactor. The productivity reached was 4.96 × 106 chlamydospores g-1 of dry substrate day-1, which is the highest productivity reported to date. The predatory capacity of the chlamydospores produced using this process was 91%. Also, a statistical control process analysis was applied, finding that the process presents stability in the biological activity, yield, and final moisture content of the substrate between batches. Finally, the operational expenses (OPEX) based on the use of the heating and humidification system were estimated, given a final cost of 0.20 USD g-1 of the fermented substrate.

Colon Cancer Prevention with Walnuts: A Longitudinal Study in Mice from the Perspective of a Gut Enterotype-like Cluster.

There is limited understanding of how walnut consumption inhibits the development of colorectal cancer. A possible mechanism may involve alterations to the gut microbiota. In this study, the effects of walnut on gut microbiota were tested in a mouse tumor bioassay using the colonotropic carcinogen, azoxymethane (AOM) added to the total Western diet (TWD). 16S rRNA pyrosequencing identified three enterotype-like clusters (E1, E2, and E3) in this murine model. E1, E2, and E3 are associated with AOM exposure, walnut consumption, and TWD diet, respectively. E2 and E3 showed distinct taxonomic and functional characteristics, while E1 represented an intermediate state. At the family level, E1 and E3 were both enriched with Bacteroidaceae, but driven by two different operational taxonomic units (OTU; OTU-2 for E1, OTU-4 for E3). E2 was overrepresented with Porphyromonadaceae and Lachnospiraceae, with OTU-3 (family Porphyromonadaceae) as the "driver" OTU for this cluster. Functionally, E3 is overrepresented with genes of glycan biosynthesis and metabolism, xenobiotic metabolism, and lipid metabolism. E2 is enriched with genes associated with cell motility, replication and repair, and amino acid metabolism. Longitudinally, E2 represents the gut microbial status of early life in these mice. In comparison with E1 and E3, E2 is associated with a moderate lower tumor burden (P = 0.12). Our results suggest that walnuts may reduce the risk of colorectal cancer within a Western diet by altering the gut microbiota. Our findings provide further evidence that colorectal cancer risk is potentially modifiable by diet via alterations to the microbiota.

Longitudinal multi-omics of host-microbe dynamics in prediabetes.

Type 2 diabetes mellitus (T2D) is a growing health problem, but little is known about its early disease stages, its effects on biological processes or the transition to clinical T2D. To understand the earliest stages of T2D better, we obtained samples from 106 healthy individuals and individuals with prediabetes over approximately four years and performed deep profiling of transcriptomes, metabolomes, cytokines, and proteomes, as well as changes in the microbiome. This rich longitudinal data set revealed many insights: first, healthy profiles are distinct among individuals while displaying diverse patterns of intra- and/or inter-personal variability. Second, extensive host and microbial changes occur during respiratory viral infections and immunization, and immunization triggers potentially protective responses that are distinct from responses to respiratory viral infections. Moreover, during respiratory viral infections, insulin-resistant participants respond differently than insulin-sensitive participants. Third, global co-association analyses among the thousands of profiled molecules reveal specific host-microbe interactions that differ between insulin-resistant and insulin-sensitive individuals. Last, we identified early personal molecular signatures in one individual that preceded the onset of T2D, including the inflammation markers interleukin-1 receptor agonist (IL-1RA) and high-sensitivity C-reactive protein (CRP) paired with xenobiotic-induced immune signalling. Our study reveals insights into pathways and responses that differ between glucose-dysregulated and healthy individuals during health and disease and provides an open-access data resource to enable further research into healthy, prediabetic and T2D states.

Integrative Personal Omics Profiles during Periods of Weight Gain and Loss.

Advances in omics technologies now allow an unprecedented level of phenotyping for human diseases, including obesity, in which individual responses to excess weight are heterogeneous and unpredictable. To aid the development of better understanding of these phenotypes, we performed a controlled longitudinal weight perturbation study combining multiple omics strategies (genomics, transcriptomics, multiple proteomics assays, metabolomics, and microbiomics) during periods of weight gain and loss in humans. Results demonstrated that: (1) weight gain is associated with the activation of strong inflammatory and hypertrophic cardiomyopathy signatures in blood; (2) although weight loss reverses some changes, a number of signatures persist, indicative of long-term physiologic changes; (3) we observed omics signatures associated with insulin resistance that may serve as novel diagnostics; (4) specific biomolecules were highly individualized and stable in response to perturbations, potentially representing stable personalized markers. Most data are available open access and serve as a valuable resource for the community.

Community characteristics of the gut microbiomes of competitive cyclists.

BACKGROUND: Changes in diet and exercise can alter the gut microbiome of humans and mice; however, few studies to date have assessed the microbiomes of highly fit athletes. In this pilot study, we used metagenomic whole genome shotgun (mWGS) and metatranscriptomic (RNA-Seq) sequencing to show what organisms are both present and active in the gut microbiomes of both professional and amateur level competitive cyclists and to determine if any significant differences exist between these two groups. RESULTS: Using mWGS sequencing data, we showed that the gut microbiomes of 33 cyclists split into three taxonomic clusters, characterized by either high Prevotella, high Bacteroides or a mix of many genera including Bacteroides, Prevotella, Eubacterium, Ruminococcus, and Akkermansia. While no significant correlations could be found between taxonomic cluster and being either a professional or amateur level cyclist, high abundance of the genus Prevotella (≥2.5%) was significantly correlated with time reported exercising during an average week. Increased abundance of Prevotella was correlated with a number of amino acid and carbohydrate metabolism pathways, including branched chain amino acid metabolism. Further analysis of the metatranscriptome revealed significant taxonomic differences when compared to the metagenome. There was increased abundance of Methanobrevibacter smithii transcripts in a number of professional cyclists in comparison to amateur cyclists and this archaeon had upregulation of genes involved in the production of methane. Furthermore, when methane metabolism was upregulated, there was similar upregulation of energy and carbohydrate metabolism pathways. CONCLUSIONS: These results provide a framework for common constituents of the gut community in individuals who follow an exercise-rich lifestyle. These data also suggest how certain organisms such as M. smithii may beneficially influence the metabolic efficiency of the gut community in professional cyclists due to synergistic metabolic cross-feeding events.

Characterization of the bacterial and fungal microbiome in indoor dust and outdoor air samples: a pilot study.

Environmental microbes have been associated with both protective and adverse health effects in children and adults. Epidemiological studies often rely on broad biomarkers of microbial exposure (i.e. endotoxin, 1 → 3-beta-d-glucan), but fail to identify the taxonomic composition of the microbial community. Our aim was to characterize the bacterial and fungal microbiome in different types of environmental samples collected in studies of human health effects. We determined the composition of microbial communities present in home, school and outdoor air samples by amplifying and sequencing regions of rRNA genes from bacteria (16S) and fungi (18S and ITS). Samples for this pilot study included indoor settled dust (from both a Boston area birth cohort study on Home Allergens and Asthma (HAA) (n = 12) and a study of school exposures and asthma symptoms (SICAS) (n = 1)), as well as fine and coarse concentrated outdoor ambient particulate (CAP) samples (n = 9). Sequencing of amplified 16S, 18S, and ITS regions was performed on the Roche-454 Life Sciences Titanium pyrosequencing platform. Indoor dust samples were dominated by Gram-positive bacteria (Firmicutes and Actinobacteria); the most abundant bacterial genera were those related to human flora (Streptococcus, Staphylococcus, Corynebacterium and Lactobacillus). Outdoor CAPs were dominated by Gram-negative Proteobacteria from water and soil sources, in particular the genera Acidovorax, and Brevundimonas (which were present at very low levels or entirely absent in indoor dust). Phylum-level fungal distributions identified by 18S or ITS regions showed very similar findings: a predominance of Ascomycota in indoor dust and Basidiomycota in outdoor CAPs. ITS sequencing of fungal genera in indoor dust showed significant proportions of Aureobasidium and Leptosphaerulina along with some contribution from Cryptococcus, Epicoccum, Aspergillus and the human commensal Malassezia. ITS sequencing detected more than 70 fungal genera in indoor dust not observed by culture. Microbiome sequencing is feasible for different types of archived environmental samples (indoor dust, and low biomass air particulate samples), and offers the potential to study how whole communities of microbes (including unculturable taxa) influence human health.

Batch, design optimization, and DNA sequencing study for continuous 1,3-propanediol production from waste glycerol by a soil-based inoculum.

1,3-propanediol (1,3-PD) was produced with a robust fermentation process using waste glycerol feedstock from biodiesel production and a soil-based bacterial inoculum. An iterative inoculation method was developed to achieve independence from soil and selectively breed bacterial populations capable of glycerol metabolism to 1,3-PD. The inoculum showed high resistance to impurities in the feedstock. 1,3-PD selectivity and yield in batch fermentations was optimized by appropriate nutrient compositions and pH control. The batch yield of 1,3-PD was maximized to ~0.7 mol/mol for industrial glycerol which was higher than that for pure glycerin. 16S rDNA sequencing results show a systematic selective enrichment of 1,3-PD producing bacteria with iterative inoculation and subsequent process control. A statistical design of experiments was carried out on industrial glycerol batches to optimize conditions, which were used to run two continuous flow stirred-tank reactor (CSTR) experiments over a period of >500 h each. A detailed analysis of steady states at three dilution rates is presented. Enhanced specific 1,3-PD productivity was observed with faster dilution rates due to lower levels of solvent degeneration. 1,3-PD productivity, specific productivity, and yield of 1.1 g/l hr, 1.5 g/g hr, and 0.6 mol/mol of glycerol were obtained at a dilution rate of 0.1 h(-1)which is bettered only by pure strains in pure glycerin feeds.

Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.