160 Search Results

Human milk fat (HMF) contains triacylglycerol (TAG) as its primary component, providing over 50% of the calories for infant nutrition, along with structural and bioactive lipids that are important for immune and nervous system development. Palmitic acid, comprising 20-25% of the fatty acid complement of HMF, is predominantly esterified to the sn -2 position on the glycerol backbone. This regiospecific positioning facilitates absorption as 2-palmitoyl-monoacylglycerol after hydrolysis of the fatty acids at sn -1 and sn -2 by gut lipases. Other features of HMF include enrichment in structured medium- and long-chain triglycerides (MLCTs), and variation in the ratio of oleicmore » acid to linoleic acid with maternal diet and geography. We have engineered Auxenochlorella, an oleaginous green alga, for biosynthesis of an MLCT- and sn -2 palmitate-enriched HMF substitute for infant formula, matching the regioisomeric composition and proportions of the most abundant fatty acids in HMF.« less

Despite advances in our understanding of bacterial plant colonization, the extent to which growth substrate influences the molecular mechanisms enabling bacteria to efficiently colonize plants remains poorly understood. To address this, we used randomly barcoded transposon mutagenesis sequencing (RB-TnSeq) in Paraburkholderia graminis OAS925, an efficient rhizosphere colonizer, and Brachypodium distachyon grown in six different substrates. Of the 382 rhizosphere colonization genes that we identified in OAS925, 348 genes (91.1%) are dependent on the growth substrate evaluated, and 34 genes (8.9%) are shared across all the substrates. Both the core and substrate-dependent colonization genes are from multiple functional categories, demonstrating themore » multifaceted and major impact that plant growth substrate has on bacterial colonization. The identified colonization genes and their varied importance across plant growth substrates could not be readily explained by differences in root exudate profiles, suggesting that the substrate environment itself plays an outsized role in the ability of a bacterium to colonize the rhizosphere. Our data confirm that bacterial fitness for plant colonization is strongly influenced by plant growth substrate type and highlights the importance of taking this parameter into consideration when engineering bacterial strains for improved host colonization.« less

Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms ofmore » MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.« less

Rice paddies significantly contribute to atmospheric methane (CH₄). Here, we show that two independent rice genotypes overexpressing genes for PLANT PEPTIDES CONTAINING SULFATED TYROSINE (PSY) reduce cumulative CH₄ emissions by 38% (PSY1) and 58% (PSY2) over 70 days of growth compared with controls. Genome-resolved metatranscriptomic data from PSY rhizosphere soils reveal lower ratios of gene activities for (mostly hydrogenotrophic) CH₄ production versus consumption, decreased activity of H₂-producing genes, and increased activity of bacterial H₂ oxidation pathways. Metabolic modeling using metagenomic and metabolomic data predicts elevated H₂ oxidation and suppressed H₂ production in the PSY rhizosphere. Assembled genomes of rhizosphere H₂-oxidizingmore » bacteria are enriched in genes utilizing gluconeogenic acids compared with H₂-producing counterparts, and their activities are likely stimulated by elevated levels of gluconeogenic acids, primarily amino acids, in PSY root exudates. Overall, our study indicates that decreased CH₄ emissions are due to a lower amount of H₂ available for hydrogenotrophic methanogenesis and provides a powerful strategy to mitigate CH₄ emissions from increasingly widespread rice cultivation.« less

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method thatmore » converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.« less

Root biology is pivotal in addressing global challenges including sustainable agriculture and climate change. However, roots have been relatively understudied among plant organs, partly due to the difficulties in imaging root structures in their natural environment. Here we used microfabricated ecosystems (EcoFABs) to establish growing environments with optical access and employed nonlinear multimodal microscopy of third-harmonic generation (THG) and three-photon fluorescence (3PF) to achieve label-free, in situ imaging of live roots and microbes at high spatiotemporal resolution. THG enabled us to observe key plant root structures including the vasculature, Casparian strips, dividing meristematic cells, and root cap cells, as wellmore » as subcellular features including nuclear envelopes, nucleoli, starch granules, and putative stress granules. THG from the cell walls of bacteria and fungi also provides label-free contrast for visualizing these microbes in the root rhizosphere. With simultaneously recorded 3PF signal, we demonstrated our ability to investigate root-microbe interactions by achieving single-bacterium tracking and subcellular imaging of fungal spores and hyphae in the rhizosphere.« less

Polyketide synthases (PKSs) are versatile biosynthetic megasynthases capable of producing a diverse range of natural products with many applications, including in pharmaceuticals. The stereochemical precision of PKSs makes them a powerful tool for engineering tailored, unnatural polyketides; however, modifying the stereocenters of a PKS product while maintaining production levels remains a significant challenge. In this study, we systematically tested and evaluated strategies for ketoreductase (KR) domain exchanges, the domain responsible for setting stereocenters of polyketide products. After first optimizing the method for KR exchanges, we then performed 44 KR domain exchanges on three different PKSs to obtain high production ofmore » all four stereoisomers in vivo. By testing both one- and two-module PKS systems, we investigated how downstream modules process intermediates with altered stereochemistry and found that the configuration of the α-substituents was critical for gatekeeping by the ketosynthase (KS). To overcome this constraint, we investigated two different strategies for altering the KS domain, including introducing targeted mutations in the downstream KS, and exploring boundaries in exchanging the entire functional unit from the donor PKS. Both strategies successfully modified the KS stereocontrol with distinct trade-offs; the functional unit exchange resulted in higher titer improvements, though it was more likely to break the entire PKS. This study demonstrates a comprehensive approach to successfully engineering all four stereochemical configurations in multiple PKS systems, advancing our understanding of and ability to rationally modify polyketide stereochemistry through multiple engineering strategies.« less

Hyperspectral imaging provides a powerful tool for analyzing above-ground plant characteristics in fabricated ecosystems, offering rich spectral information across diverse wavelengths. This study presents an efficient workflow for hyperspectral data segmentation and subsequent data analytics, minimizing the need for user annotation through the use of ensembles of sparse mixed scale convolution neural networks. The segmentation process leverages the diversity of ensembles to achieve high accuracy with minimal labeled data, reducing labor-intensive annotation efforts. To further enhance robustness, we incorporate image alignment techniques to address spatial variability in the dataset. Downstream analysis focuses on using the segmented data for processing spectralmore » data, enabling monitoring of plant health. This approach provides a scalable solution for spectral segmentation, and facilitates actionable insights into plant conditions in complex, controlled environments. Our results demonstrate the utility of combining advanced machine learning techniques with hyperspectral analytics for high-throughput plant monitoring.« less

Background Incorporating the production of related ligninolytic enzymes into industrial filamentous fungus Aspergillus niger will enhance the bioconversion of lignocelluloses to various chemical products. Results In this study, transgenic expression of Phanerochaete chrysosporium manganese peroxidases (mnps) and Trametes sp. C30 laccase hybrid Lac131 (lac131) were examined and optimized in A. niger 11414 prtT∆ strain. Five mnps (mnp1, mnp2, mnp3, mnp4, and mnp5) and lac131 genes were expressed separately or in combination. The transgenic strain containing the entire mnp2 genomic coding sequence (gmnp2) exhibited the highest mnP activity among the five mnp over-expression strains in the modified minimal medium (mMM) withmore » addition of 5 g/L bovine hemoglobin (bHg). We examined the effects of hemin and bHg on mnP production in the gmnp2 strain cultures and found that at least 1 g/L bHg was required, while hemin was not. Culture conditions for mnP production were further optimized for the gmnp2 strain and the highest mnP activities were detected in the cultures grown at 25 °C and 200 rpm with an initial pH of 4.5. Effects of soy protein, skim milk, and bovine serum albumin on mnP production were investigated; 5 g/L of soy proteins or skim milk had comparable effects to 2.5 g/L bHg, while cultures with bovine serum albumin had diminished mnP activity. Disruption of both prtT and vsm1 substantially augmented the mnP production and its activity reached 575 U/L. Trametes sp. C30 laccase hybrid lac131 was strongly expressed in either A. niger gmnp2 (1975 U/L) or 11414prtT∆ (3895 U/L) strain. Both mnP and laccase in the culture supernatants effectively decolorized selected phenolic compounds (dyes) and cleaved tagged model lignin dimers. Conclusion The mnP was successfully produced in A. niger by optimizing the culture conditions and host strain. Co-expression of all four mnp genes in the same expression host by multiplex CRISPR will lead to the mnP production reaching levels comparable to P. chrysosporium, while only requiring 36 h at 25 °C. The Lac131 activity in transgenic A. niger strain is 4- to 7-times higher than that in previous studies. Co-production of mnP and laccase in A. niger will enhance the lignin bioconversion efficiency.« less

The interdisciplinary nature of microbiome research, coupled with the generation of complex multi-omics data, makes knowledge sharing challenging. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines provide a checklist for the reporting of study information, experimental design and analytical methods within a scientific manuscript on human microbiome research. Here, in this Consensus Statement, we present the standards for technical reporting in environmental and host-associated microbiome studies (STREAMS) guidelines. The guidelines expand on STORMS and include 67 items to support the reporting and review of environmental (for example, terrestrial, aquatic, atmospheric and engineered), synthetic and non-human host-associated microbiomemore » studies in a standardized and machine-actionable manner. Based on input from 248 researchers spanning 28 countries, we provide detailed guidance, including comparisons with STORMS, and case studies that demonstrate the usage of the STREAMS guidelines. In conclusion, STREAMS, like STORMS, will be a living community resource updated by the Consortium with consensus-building input of the broader community.« less