Biology subjects

Feist, A.

Publications and source records attributed to Feist, A..

15 recordsLinked to original sources

bioRxiv2026

Adaptive laboratory evolution rewires Pseudomonas putida for resource-efficient acetate assimilation

Acetate is an attractive renewable two-carbon substrate for microbial biotechnology, but its toxicity limits growth and carbon-use efficiency at process-relevant concentrations. Here, we used adaptive laboratory evolution to improve acetate tolerance in a genome-reduced strain of Pseudomonas putida and combined whole-genome sequencing, reverse engineering, transcriptomics, proteomics, and 13C-acetate fluxomics to resolve the underlying adaptation mechanisms. Evolution under increasing acetate concentrations selected recurrent mutations in gacA and fabB, which encode a global response regulator and a fatty acid biosynthesis enzyme, respectively. Reverse engineering of these mutations recovered most of the evolved phenotype, including shorter lag phase and substantially higher biomass yield from acetate. Multi-omic analyses showed repression of type VI secretion systems, carbohydrate storage functions, fatty acid metabolism, and oxidative stress-associated proteins, indicating resource reallocation away from costly stress and non-essential programs. Fluxomics further revealed reduced EDEMP cycling and increased glyoxylate shunt flux, consistent with improved acetate-carbon retention in biomass. These results establish acetate tolerance in P. putida as a resource-efficiency phenotype and identify gacA and fabB as actionable targets for acetate-based bioproduction.

synthetic biology↗

bioRxiv2026

Haplotype-phased genomes of the barley leaf rust pathogen reveal evidence of repeat element expansion and somatic hybridization

Barley leaf rust disease, caused by Puccinia hordei, leads to substantial yield losses and diminished malting quality of barley across temperate growing regions worldwide. To address the paucity of high-resolution genomic resources for this pathogen, we generated haplotype-phased, chromosome-scale assemblies for ten globally distributed isolates using PacBio HiFi and Hi-C sequencing. Phylogenomic analysis revealed seven distinct lineages of P. hordei, including evidence of nuclear exchange, with a shared nuclear haplotype detected between two US lineages. Nuclear genome sizes ranged from [~]140-147Mbp, with the exception of isolate 90ISR03 from Israel ([~]163Mbp), which also harbored a 6.2Mbp supernumerary scaffold in one nucleus exhibiting chromosomal characteristics. Consistent with its larger genome, P. hordei had a higher repeat content ([~]70%) than related cereal rust fungi, driven primarily by the proliferation of LTR retroelements and DNA transposons. Across the global pan-genome of 13 unique nuclear haplotypes, approximately one-third of all protein orthogroups were conserved across all isolates. Only 18% of predicted effector orthogroups were shared between all haplotypes, reflecting the highly dynamic and variable nature of the effector repertoire. The long-term propagation of clonal P. hordei lineages is apparent both within the US and globally, and nuclear exchange is important for generating novel diversity and virulence profiles. The high degree of genome plasticity is evident in extensive structural variation, including large-scale translocations and inversions as well as a putative accessory chromosome. These chromosome-level, haplotype-resolved genomes provide a foundational resource for exploring the evolution, diversity, and avirulence gene repertoire of P. hordei.

genomics↗

bioRxiv2024

Scalable Fabrication of a Tough and Recyclable Spore-Bearing Biocomposite Thermoplastic Polyurethane

Thermoplastic polyurethanes (TPUs) are a class of versatile thermoplastic elastomers where most of their products lack a proper recycling strategy or have no end-of-life solutions. To pursue a sustainable end-of-life solution for TPU based products, self-disintegrating biocomposite TPUs have recently been developed by embedding spores of TPU-degrading bacteria into TPUs using melt extrusion. Herein, we improve upon spore-bearing biocomposites and demonstrate industrially-relevant manufacturing conditions for the fabrication of biocomposite TPUs. Spore production was modified to reduce the innate brown color of the resulting materials and, effectively minimize the coloration of biocomposite TPUs. Reduction of FeSO4 in a sporulation media generated white spores without compromising spore productivity, viability, morphology or heat-shock tolerance. Biocomposite TPUs containing white spores displayed a 45% increase in toughness compared to TPUs without spores, while retaining [~]90% spore viability post processing. Furthermore, biocomposite TPU fabrication was demonstrated using a scalable continuous extruder followed by injection molding. Biocomposite TPUs generated by these industry-relevant processes exhibited comparable toughness improvement and spore viability to biocomposite TPU prepared using a lab scale microcompounder, while enhancing productivity by 30-fold. Finally, spore addition improved biocomposite TPUs recyclability, enabling 80% toughness retention after 5 rounds of iterative melt processing. Additionally, no negative effect on the lifespan of the generated TPUs was observed over a duration of 1 year of storage. Overall, this study confirmed that spore-bearing biocomposite TPUs are promising for practical applications, offering an accessible method to enhance toughness and sustainability of commercial TPUs through the incorporation of spore-based living fillers.

bioengineering↗

bioRxiv2024

Discovery of functional NLRs using expression level, high-throughput transformation, and large-scale phenotyping

Protecting crops from pests and diseases is vital for the sustainable agricultural systems needed for food security. Introducing functional resistance genes to enhance the plant immune system is an effective method of disease control, but identifying new immune receptors is time-consuming and resource intensive. We observed that functional immune receptors of the NLR class show a signature of high expression in uninfected plants across both monocot and dicot species. Here we show that this signature, combined with high throughput crop transformation, can be used to rapidly identify candidate NLRs from diverse plant species and validate pathogen resistance directly in crop plants. As a proof of concept, we generated a wheat transgenic library carrying 995 NLRs from 18 grass species. Screening the collection with the stem rust pathogen Puccinia graminis, which is a major threat to wheat production, we confirm 19 new resistance genes. This pipeline facilitates resistance gene discovery, unlocking a large gene pool of diverse and non-domesticated plant species and providing in-planta gene validation of disease resistance directly in crops.

plant biology↗

bioRxiv2022

Revealing Pentose Catabolism in Pseudomonas putida

The Pseudomonas putida group in the Gammaproteobacteria has been intensively studied for bioremediation and plant growth promotion. Members of this group have recently emerged as promising hosts to convert intermediates derived from plant biomass to biofuels and biochemicals. However, most strains of P. putida cannot metabolize pentose sugars derived from hemicellulose. Here we describe three isolates that provide a broader view of the pentose sugar catabolism in the P. putida group. One of these isolates clusters with the well-characterized P. alloputida KT2440 (strain BP6); the second isolate clustered with plant growth-promoting strain P. putida W619 (strain M2), while the third isolate represents a new species in the group (strain BP8). Each of these isolates possessed homologous genes for oxidative xylose catabolism (xylDXA) and a potential xylonate transporter. Strain M2 grew on arabinose and had genes for oxidative arabinose catabolism (araDXA). A CRISPRi system was developed for strain M2 and identified conditionally essential genes for xylose growth. A glucose dehydrogenase was found to be responsible for initial oxidation of xylose and arabinose in strain M2. These isolates have illuminated inherent diversity in pentose catabolism in the P. putida group and may provide alternative hosts for biomass conversion. Originality-Significance StatementMembers of the Pseudomonas putida group are intensively studied for their role in plant growth promotion and biomass conversion. Despite this interest, the scope of pentose oxidation, key sugars in plant biomass, in this group is not known. Here, we report targeted isolation of members of the P. putida group that grow by xylose and arabinose oxidation. Using a combined genomic and proteomic approach, we identify gene products involved in pentose oxidation and identify conditionally essential genes for xylose oxidation using a CRISPRi gene repression approach. This work describes a targeted isolation and analysis strategy that may applied for many microbial groups of industrial and agricultural interest.

microbiology↗

bioRxiv2022

Laboratory evolution of synthetic electron transport system variants reveals a larger metabolic respiratory system and its plasticity

Respiration requires organisms to have an electron transport system (ETS) for the generation of proton motive force across the membrane that drives ATP synthase. Although the molecular details of the ETS are well studied and constitute textbook material, few studies have appeared to elucidate its systems biology. The most thermodynamically efficient ETS consists of two enzymes, an NADH: quinone oxidoreductase (NqRED) and a dioxygen reductase (O2RED), which facilitate the shuttling of electrons from NADH to oxygen. However, evolution has produced variations within ETS which modulate the overall energy efficiency of the system even within the same organism 1-3. The system-level impact of these variations and their individual physiological optimality remain poorly determined. To mimic varying ETS efficiency we generated four Escherichia coli deletion strains (named ETS-1H, 2H, 3H, and 4H) harboring unbranched ETS variants that pump 1, 2, 3, or 4 proton(s) per electron respectively. We then used a combination of synergistic methods (laboratory evolution, multi-omic analyses, and computation of proteome allocation) to characterize these ETS variants. We found that: (a) all four ETS variants evolved to a similar optimized growth rate, (b) the evolution of ETS variants was enabled by specific rewiring of major energy-generating pathways that couple to the ETS to optimize their ATP production capability, (c) proteome allocation per ATP generated was the same for all the variants, (d) the aero-type, that designates the overall ATP generation strategy 4 of a variant, remained conserved during its laboratory evolution, with the exception of the ETS-4H variant, and (e) integrated computational analysis of then data supported a proton-to-ATP ratio of 10 protons per 3 ATP for ATP synthase for all four ETS variants. We thus have defined the Aero-Type System (ATS) as a generalization of the aerobic bioenergetics, which is descriptive of the metabolic systems biology of respiration and demonstrates its plasticity.

systems biology↗

bioRxiv2021

Data-Driven Strain Design Using Aggregated Adaptive Laboratory Evolution Mutational Data

Microbes are being engineered for an increasingly large and diverse set of applications. However, the designing of microbial genomes remains challenging due to the general complexity of biological system. Adaptive Laboratory Evolution (ALE) leverages natures problem-solving processes to generate optimized genotypes currently inaccessible to rational methods. The large amount of public ALE data now represents a new opportunity for data-driven strain design. This study presents a novel and first of its kind meta-analysis workflow to derive data-driven strain designs from aggregate ALE mutational data using rich mutation annotations, statistical and structural biology methods. The mutational dataset consolidated and utilized in this study contained 63 Escherichia coli K-12 MG1655 based ALE experiments, described by 93 unique environmental conditions, 357 independent evolutions, and 13,957 observed mutations. High-level trends across the entire dataset were established and revealed that ALE-derived strain designs will largely be gene-centric, as opposed to non-coding, and a relatively small number of variants (approx. 4) can significantly alter cellular states and provide benefits which range from an increase in fitness to a complete necessity for survival. Three novel experimentally validated designs relevant to metabolic engineering applications are presented as use cases for the workflow. Specifically, these designs increased growth rates with glycerol as a carbon source through a point mutation to glpK and a truncation to cyaA or increased tolerance to toxic levels of isobutyric acid through a pykF truncation. These results demonstrate how strain designs can be extracted from aggregated ALE data to enhance strain design efforts. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/452699v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@8e1759org.highwire.dtl.DTLVardef@9ee7d5org.highwire.dtl.DTLVardef@866f04org.highwire.dtl.DTLVardef@1e27b29_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2021

Selection for cell yield does not reduce overflow metabolism in E. coli

Overflow metabolism is ubiquitous in nature, and it is often considered inefficient because it leads to a relatively low biomass yield per consumed carbon. This metabolic strategy has been described as advantageous because it supports high growth rates during nutrient competition. Here we experimentally evolved bacteria without nutrient competition by repeatedly growing and mixing millions of parallel batch cultures of E. coli. Each culture originated from a water-in-oil emulsion droplet seeded with a single cell. Unexpectedly we found that overflow metabolism (acetate production) did not change. Instead the numerical cell yield during the consumption of the accumulated acetate increased as a consequence of a reduction in cell size. Our experiments and a mathematical model show that fast growth and overflow metabolism followed by the consumption of the overflow metabolite, leads to a higher numerical cell yield and therefore a higher fitness compared to full respiration of the substrate. This provides an evolutionary scenario where overflow metabolism can be favourable even in the absence of nutrient competition.

microbiology↗

bioRxiv2020

Characterizing the response of Acinetobacter baumannii ATCC 17978 to azithromycin in multiple in vitro growth conditions

Multi-drug resistant (MDR) Acinetobacter baumannii is one of the most concerning pathogens in hospital infections. A. baumannii is categorized as an "Urgent Threat" by the U.S. Centers for Disease Control and the highest priority pathogen by the World Health Organization due to its propensity for broad antibiotic resistance and its associated high mortality rates. New treatment options are urgently needed for MDR A. baumannii infections. Our prior studies have demonstrated an unappreciated utility of the macrolide azithromycin (AZM) against MDR A. baumannii in tissue-culture medium. This finding is all the more surprising since AZM has no appreciable activity against A. baumannii in standard bacteriological media. The basis for this media-dependent activity of AZM against A. baumannii is not fully defined. In this study, we utilize a variety of techniques (growth dynamics, bacterial cytological profiling, RNA sequencing, and LC/MS) to profile the response of MDR A. baumannii to AZM in both standard bacteriological and more physiological relevant mammalian tissue-culture medium. [Table 1]

microbiology↗

bioRxiv2020

Laboratory evolution of multiple E. coli strains reveals unifying principles of adaptation but diversity in driving genotypes

Fitness landscapes are a central concept in evolutionary biology and have been thoroughly detailed in terms of genotypes. However, our understanding of the selected metabolic and gene expression adaptations, and their dependence on genetic background, remains limited. Here, we reveal multi-scale adaptation principles in the E. coli species by taking multi-omics measurements of six different strains throughout their adaptive evolution to glucose minimal media. Statistics and matrix factorization is applied to yield four key results. First, analysis of the metabolic and physiological data shows evolutionary convergence in growth rate, glucose uptake rate, glycolytic ATP and NADH production but divergence in NADPH production strategies. Second, factorization-based analysis of the transcriptome revealed six conserved transcriptomic adaptations describing increased expression of ribosome and amino acid biosynthetic genes and decreased expression of stress response and structural genes. Third, correlation analysis identifies five tradeoffs underlying the transcriptomic profiles. Fourth, statistical tests leveraging ALE design identify four mutation-flux correlates and eight mutation-transcriptomic correlates that link mutations to systems level adaptation principles. Our total results reveal the dominant metabolic and regulatory constraints governing E. coli growth adaptation that either distinguish strains or are conserved principles.

systems biology↗

bioRxiv2020

Identifying the effect of vancomycin on HA-MRSA strains using bacteriological and physiological media

Healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) USA100 strains are of major concern due to their evolving antibiotic resistant. They are resistant to a broad class of antibiotics like macrolides, aminoglycosides, fluoroquinolones, and many more. The selection of appropriate antibiotic susceptibility examination media is very important. Thus, we use bacteriological (CA-MHB) as well as physiological (R10LB) media to determine the effect of vancomycin on USA100 strains. The study includes the profiling behaviour of HA-MRSA USA100 D592 and D712 strains in the presence of vancomycin through various high-throughput assays. The US100 D592 and D712 strains were characterized at sub-inhibitory concentrations through growth curves, RNA sequencing, bacterial cytological profiling, and exo-metabolomics high throughput experiments. The study reveals the vancomycin resistance behavior of USA100 strains in dual media conditions using wide-ranging experiments.

microbiology↗

bioRxiv2020

Decomposition of transcriptional responses provides insights into differential antibiotic susceptibility

Responses of bacteria to antibiotic treatments depend on their environments. Differences between in vitro testing conditions and the physiological environments inside patients have resulted in poor antibiotic susceptibility predictions, contributing to treatment failures in the clinic. Here, we investigate how media composition affects antibiotic susceptibility in the laboratory strain E. coli K-12 MG1655, and contextualize these changes through machine learning of transcriptomics data. We show that complex transcriptional changes induced by different media or antibiotic treatment can be traced back to a few key regulators. Integration of results from machine learning with biochemical knowledge reveals fundamental shifts in respiration and iron availability that may explain media-dependent differential susceptibility to antibiotics. The data generation and analytical workflow used here can interrogate the regulatory state of a pathogen under any condition, and can be extended to additional strains and organisms for which data is available.

microbiology↗

bioRxiv2020

Profiling the effect of nafcillin on HA-MRSA D592 using bacteriological and physiological media

Staphylococcus aureus is a leading human pathogen associated with both hospital-acquired and community-acquired infections. The bacterium has steadily gained resistance to {beta}-lactams and other important first-line antibiotics culminating in its categorization as an urgent threat by the U.S. Centers for Disease Control and Prevention. Observations of a varying response to antimicrobial exposure as a function of media type has revealed that clinical susceptibility testing performed in standard bacteriological media might not adequately represent pharmacological responses in the patient. Such observations have encouraged research designed to identify media types that more closely mimic the in vivo environment. In this study, we examine the response of a hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate S. aureus (MRSA/VISA) strain (D592) to nafcillin in a bacteriological compared to a more physiological tissue culture-based medium. We performed multi-dimensional analysis including growth and bacterial cytological profiling, RNA sequencing, and exo-metabolomics measurements (both HPLC and LC/MS) to shed light on the media-dependent activity of the commonly prescribed {beta}-lactam antibiotic nafcillin. O_TBL View this table: org.highwire.dtl.DTLVardef@85b95borg.highwire.dtl.DTLVardef@14c1504org.highwire.dtl.DTLVardef@1f7e976org.highwire.dtl.DTLVardef@100598dorg.highwire.dtl.DTLVardef@1f770e9_HPS_FORMAT_FIGEXP M_TBL C_TBL

microbiology↗

bioRxiv2018

Model-driven design and evolution of non-trivial synthetic syntrophic pairs

Synthetic microbial communities are attractive for applied biotechnology and healthcare applications through their ability to efficiently partition complex metabolic functions. By pairing auxotrophic mutants in co-culture, nascent E. coli communities can be established where strain pairs are metabolically coupled. Intuitive synthetic communities have been demonstrated, but the full space of cross-feeding metabolites has yet to be explored. A novel algorithm, OptAux, was constructed to design 66 multi-knockout E. coli auxotrophic strains that require significant metabolite cross-feeding when paired in co-culture. Three OptAux predicted auxotrophic strains were co-cultured with an L-histidine auxotroph and validated via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community fitness and provided insights on mechanisms for sharing and adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents a novel computational method to elucidate metabolic changes that empower community formation and thus guide the optimization of co-cultures for a desired application.

systems biology↗

bioRxiv2018

ALEdb 1.0: A Database of Mutations from Adaptive Laboratory Evolution

Full genomic sequences are readily available, but their functional interpretation remains a fundamental challenge. Adaptive Laboratory Evolution (ALE) has emerged as an experimental approach to discover causal mutations that confer desired phenotypic functions. Thus, ALE not only represents a controllable experimental approach to systematically discover genotype-phenotype relationships, but it also allows for the revelation of the series of genetic alterations required to acquire the new phenotype. Numerous ALE studies have appeared in the literature providing a strong impetus for developing structured databases to warehouse experimental evolution information and make it retrievable for large-scale analysis. Here, the first step towards establishing this capability is presented: ALEdb (http://aledb.org). This initial release contains over 11,000 mutations that have been discovered in ALE experiments. ALEdb is the first of its kind; (1) it is a web-based platform that comprehensively reports on ALE acquired mutations and their conditions, (2) it reports key mutations using previously established trends, (3) it enables a search-driven workflow to enhance user mutation functional analysis, (4) it allows exporting of mutation query results for custom analysis, (5) it has a bibliome that describes the underlying published literature, and (6) contains experimental evolution mutations from multiple model organisms. Thus, ALEdb is an informative platform which will become increasingly revealing as the number of reported ALE experiments and identified mutations continue to expand.

bioinformatics↗