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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗
DOE OSTI2015

The challenges of modelling antibody repertoire dynamics in HIV infection

Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selection and compare this to the observed temporal patterns of antibody evolution in HIV infection. In addition, we describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

Current diagnostics and clinical management strategies for combat wounds are based on decisions made by expert clinicians. However, even in the hands of experienced surgeons, wounds from combat injuries can exhibit failed healing and complications related to limitations in the rapid and comprehensive generation of diagnostic information. Previous studies have demonstrated the possible use of genomic sequencing approaches to detect microbial signatures involved in combat casualty care. While effective, whole metagenome sequencing is limited by the depth required to confidently detect all relevant signatures. To address this, we developed a targeted capture sequencing panel to detect microbial signatures relevant to wound healing. These targets include known microbial nosocomial pathogens, wound colonizers, and genes involved in virulence and antimicrobial resistance. A bioinformatics pipeline was built to identify genomic regions of interest and over 8,000 oligonucleotide probes were designed for capture. The panel was synthesized and validated using control reference genomes in human background and on wound-effluent samples from a cohort of combat-injured U.S. service members. Our panel was sensitive against wound-colonizing species, Acinetobacter baumannii and Pseudomonas aeruginosa, and was specific in detecting corresponding virulence and antimicrobial-resistance genes as well as other pathogenic species present in microflora mixtures. Random forest feature permutation confirmed the prevalence of Acinetobacter and Pseudomonas in critically colonized wounds and wounds that failed to heal, respectively. Our results demonstrate the capability of targeted sequencing tools and analysis platforms to profile and deliver information on pathogenic factors influencing wound progression, thereby guiding therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

RNA‐Seq analysis revealed the molecular mechanisms of photobiomodulation effect on human fibroblasts

Abstract Background The photobiomodulation (PBM) effect has been applied to various clinical therapy for a long time. However, the mechanism related to the PBM effect in terms of wavelengths has been lack of in‐depth study, except that ultraviolet radiation has attracted much attention due to its strong cell‐killing effect. Purpose To clarify the principle behind PBM and the main mechanism of improvement. Methods To carry on this study, we created light equipment using three LED chips, which emit 390 nm ultraviolet radiation, 415 nm blue light and 660 nm red light, respectively. We choose human fibroblasts (HF) to be irradiated by three different wavelengths for PBM test. In this study, we used cell counting kit (CCK‐8) test to show the cell proliferation roughly and reported on a systematic RNA sequencing (RNA‐seq) analysis at transcriptional expression levels from HF, which accepted PBM of different wavelengths of light. Results We found that 415 nm blue light inhibited cell proliferation and 660 nm red light stimulated cell proliferation while 390 nm ultraviolet radiation has little influence on cell proliferation. Furthermore, RNA‐seq results showed that CSF1R, PPP3CC, ITGAL, ITGAM, IL2RB, and several other differentially expressed genes (DEGs) are involved in the cell proliferation. Relative DEGs values for matrix metalloproteinases (MMPs) gene family have shown a great difference in blue and red light radiation especially on MMP25, MMP9, MMP21, and MMP13. Conclusion Taken together, the results provide a valuable resource to describe the variation of HFs under PBM of different light at gene level.

Li, Wenqi↗
DOE OSTI2015

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping error rates low, as well as offering unique data visualization options.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Correlation of structure, function and protein dynamics in GH7 cellobiohydrolases from Trichoderma atroviride, T. reesei and T. harzianum

The ascomycete fungus Trichoderma reesei is the predominant source of enzymes for industrial conversion of lignocellulose. Its glycoside hydrolase family 7 cellobiohydrolase (GH7 CBH) TreCel7A constitutes nearly half of the enzyme cocktail by weight and is the major workhorse in the cellulose hydrolysis process. The orthologs from Trichoderma atroviride (TatCel7A) and Trichoderma harzianum (ThaCel7A) show high sequence identity with TreCel7A, ~ 80%, and represent naturally evolved combinations of cellulose-binding tunnel-enclosing loop motifs, which have been suggested to influence intrinsic cellobiohydrolase properties, such as endo-initiation, processivity, and off-rate. The TatCel7A, ThaCel7A, and TreCel7A enzymes were characterized for comparison of function. The catalytic domain of TatCel7A was crystallized, and two structures were determined: without ligand and with thio-cellotriose in the active site. Initial hydrolysis of bacterial cellulose was faster with TatCel7A than either ThaCel7A or TreCel7A. In synergistic saccharification of pretreated corn stover, both TatCel7A and ThaCel7A were more efficient than TreCel7A, although TatCel7A was more sensitive to thermal inactivation. Structural analyses and molecular dynamics (MD) simulations were performed to elucidate important structure/function correlations. Moreover, reverse conservation analysis (RCA) of sequence diversity revealed divergent regions of interest located outside the cellulose-binding tunnel of Trichoderma spp. GH7 CBHs. We hypothesize that the combination of loop motifs is the main determinant for the observed differences in Cel7A activity on cellulosic substrates. Fine-tuning of the loop flexibility appears to be an important evolutionary target in Trichoderma spp., a conclusion supported by the RCA data. Our results indicate that, for industrial use, it would be beneficial to combine loop motifs from TatCel7A with the thermostability features of TreCel7A. Furthermore, one region implicated in thermal unfolding is suggested as a primary target for protein engineering.

09 BIOMASS FUELS↗
DOE OSTI2023

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗
DOE OSTI2018

Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias

Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Optimization models for integrated biorefinery operations

Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.

09 BIOMASS FUELS↗
DOE OSTI2017

Identification and functional characterization of three type III polyketide synthases from Aquilaria sinensis calli

Type III polyketide synthases (PKSs) play an important role in biosynthesis of various plant secondary metabolites and plant adaptation to environmental stresses. Aquilaria sinensis (A. sinensis) is the main plant species for production of agarwood, little is known about its PKS family. In this study, AsCHS1 and two new type III PKSs, AsPKS1 and AsPKS2, were isolated and characterized in A. sinensis calli. The comparative sequence and phylogenetic analysis indicated that AsPKS1 and AsPKS2 belonged to non-CHS group different from AsCHS1. The recombinant AsPKS1 and AsPKS2 produced the lactone-type products, suggesting their different enzyme activities from AsCHS1. Three PKS genes had a tissues-specific pattern in A. sinensis. Moreover, we examined the expression profiles of three PKS genes in calli under different abiotic stresses and hormone treatments. AsCHS1 transcript was most significantly induced by salt stress, AsPKS1 abundance was most remarkably enhanced by CdCl{sub 2} treatment, while AsPKS2 expression was most significantly induced by mannitol treatment. Furthermore, AsCHS1, AsPKS1 and AsPKS2 expression was enhanced upon gibberellins (GA3), methyl jasmonate (MeJA), or salicylic acid (SA) treatment, while three PKS genes displayed low transcript levels at the early stage under abscisic acid (ABA) treatment. In addition, three GFP:PKSs fusion proteins were localized in the cytoplasm and cell wall in Nicotiana benthamiana cells. These results indicated the multifunctional role of three type III PKSs in polyketide biosynthesis, plant resistance to abiotic stresses and signal transduction. - Highlights: • Two new PKS genes (AsPKS1 and AsPKS2) were isolated and characterized from A. sinensis. • The recombinant AsPKS1 and AsPKS2 catalyzed lactone-type products in vitro. • AsCHS1, AsPKS1 and AsPKS2 were involved in plant responses to abiotic stresses and hormone stimuli. • Our results also indicated that AsCHS1, AsPKS1 and AsPKS2 were predominantly localized in the cytoplasm and cell wall.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Homology modeling and docking of AahII-Nanobody complexes reveal the epitope binding site on AahII scorpion toxin

Highlights: • AahII specific nanobodies share common CDRs sequence patterns. • Residues forming sequences' pattern interact specifically with AahII. • CDR1 Tyr27, Tyr29 and Ser30 polar residues are involved in AahII neutralization. • Interacting AahII Arg62/NbAahII10 CDR3 Asp112 charged residues are crucial. • AahII-NbAahII10 trapping involves a distinct toxin 3D orientation. Scorpion envenoming and its treatment is a public health problem in many parts of the world due to highly toxic venom polypeptides diffusing rapidly within the body of severely envenomed victims. Recently, 38 AahII-specific Nanobody sequences (Nbs) were retrieved from which the performance of NbAahII10 nanobody candidate, to neutralize the most poisonous venom compound namely AahII acting on sodium channels, was established. Herein, structural computational approach is conducted to elucidate the Nb-AahII interactions that support the biological characteristics, using Nb multiple sequence alignment (MSA) followed by modeling and molecular docking investigations (RosettaAntibody, ZDOCK software tools). Sequence and structural analysis showed two dissimilar residues of NbAahII10 CDR1 (Tyr27 and Tyr29) and an inserted polar residue Ser30 that appear to play an important role. Indeed, CDR3 region of NbAahII10 is characterized by a specific Met104 and two negatively charged residues Asp115 and Asp117. Complex dockings reveal that NbAahII17 and NbAahII38 share one common binding site on the surface of the AahII toxin divergent from the NbAahII10 one's. At least, a couple of NbAahII10 – AahII residue interactions (Gln38 – Asn44 and Arg62, His64, respectively) are mainly involved in the toxic AahII binding site. Altogether, this study gives valuable insights in the design and development of next generation of antivenom.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Systematic identification of transcriptional activation domains from non-transcription factor proteins in plants and yeast

Transcription factors can promote gene expression through activation domains. Whole-genome screens have systematically mapped activation domains in transcription factors but not in non-transcription factor proteins (e.g., chromatin regulators and coactivators). To fill this knowledge gap, we employed the activation domain predictor PADDLE to analyze the proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae. We screened 18,000 predicted activation domains from >800 non-transcription factor genes in both species, confirming that 89% of candidate proteins contain active fragments. Our work enables the annotation of hundreds of nuclear proteins as putative coactivators, many of which have never been ascribed any function in plants. Analysis of peptide sequence compositions reveals how the distribution of key amino acids dictates activity. Finally, we validated short, "universal" activation domains with comparable performance to state-of-the-art activation domains used for genome engineering. Our approach enables the genome-wide discovery and annotation of activation domains that can function across diverse eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Comparative genomics provides insights into the cold adaptation of endophytic fungi associated with Deschampsia antarctica

Endophytic fungi from Deschampsia antarctica , the southernmost flowering plant, provide insights into the cold adaptation mechanisms of plant-associated fungi in extreme environments. This study presents the genome sequences and comparative analysis of eight fungal isolates from D. antarctica leaves. These Antarctic fungal isolates were analyzed alongside 121 plant-associated fungal genomes to uncover signatures of adaptation and endophytic specialization. Antarctic endophytes show striking patterns, including reduced genome size (∼26.3 Mb on average), streamlined gene content (∼8844 genes), and notably small secretomes (∼288 proteins). Despite this reduced gene repertoire, they maintain a robust set of genes encoding carbohydrate-active enzymes (CAZymes) but lack those for lignin and bacterial cell wall degradation, indicating a symbiotic lifestyle that avoids host damage and predation. One isolate, Alternaria sp. UNIPAMPA017 stood out, with 26% of its genome occupied by transposable elements. Lifestyle, rather than phylogeny, was the main driver of CAZyme and secretome profiles, underscoring ecological convergence. Compared to endophytes from Arabidopsis and Populus, D. antarctica endophytes harbor fewer pectin-degrading enzymes, reflecting their adaptation to the cell wall structure of their monocot host. Together, these fungi reveal a pattern of genomic reduction and functional fine-tuning, hallmarks of life adapted to persist in cold, nutrient-scarce niches.

Ascomycota↗
DOE OSTI2023

Metabolic engineering of low-pH-tolerant non-model yeast, Issatchenkia orientalis , for production of citramalate

Methyl methacrylate (MMA) is an important petrochemical with many applications. However, its manufacture has a large environmental footprint. Combined biological and chemical synthesis (semisynthesis) may be a promising alternative to reduce both cost and environmental impact, but strains that can produce the MMA precursor (citramalate) at low pH are required. A non-conventional yeast, Issatchenkia orientalis, may prove ideal, as it can survive extremely low pH. Here, we demonstrate the engineering of I. orientalis for citramalate pro- duction. Using sequence similarity network analysis and subsequent DNA synthesis, we selected a more active citramalate synthase gene (cimA) variant for expression in I. orientalis. We then adapted a piggyBac transposon system for I. orientalis that allowed us to simultaneously explore the effects of different cimA gene copy numbers and integration locations. A batch fermentation showed the genome-integrated-cimA strains produced 2.0 g/L citramalate in 48 h and a yield of up to 7% mol citramalate/mol consumed glucose. These results demonstrate the potential of I. orientalis as a chassis for citramalate production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A novel pathogenic aviadenovirus from red-bellied parrots (Poicephalus rufiventris) unveils deep recombination events among avian host lineages

Competing roles of coevolution, selective pressure and recombination are an emerging interest in virus evolution. We report a novel aviadenovirus from captive red-bellied parrots (Poicephalus rufiventris) that uncovers evidence of deep recombination among aviadenoviruses. The sequence identity of the virus was most closely related to Turkey adenovirus D (42% similarity) and other adenoviruses in chickens, turkeys and pigeons. Sequencing and comparative analysis showed that the genome comprised 40,930 nucleotides containing 42 predicted open reading frames (ORFs) 19 of which had strong similarity with genes from other adenovirus species. The new genome unveiled a lineage that likely participated in deep recombination events across the genus Aviadenovirus accounting for an ancient evolutionary relationship. We hypothesize frequent host switch events and recombination among adenovirus progenitors in Galloanserae hosts caused the radiation of extant aviadenoviruses and the newly assembled Poicephalus adenovirus genome points to a potentially broader host range of these viruses among birds. - Highlights: •Shows how a single new genome can change overall phylogeny. •Reveals host switch events among adenovirus progenitors in Galloanserae hosts. •Points to a potentially broader host range of adenoviruses among birds and wildlife .

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Predicting Anaerobic Membrane Bioreactor Performance Using Flow-Cytometry-Derived High and Low Nucleic Acid Content Cells

Having a tool to monitor the microbial abundances rapidly and to utilize the data to predict the reactor performance would facilitate the operation of an anaerobic membrane bioreactor (AnMBR). This study aims to achieve the aforementioned scenario by developing a linear regression model that incorporates a time-lagging mode. The model uses low nucleic acid (LNA) cell numbers and the ratio of high nucleic acid (HNA) to LNA cells as an input data set. First, the model was trained using data sets obtained from a 35 L pilot-scale AnMBR. The model was able to predict the chemical oxygen demand (COD) removal efficiency and methane production 3.5 days in advance. Subsequent validation of the model using flow cytometry (FCM)-derived data (at time t – 3.5 days) obtained from another biologically independent reactor did not exhibit any substantial difference between predicted and actual measurements of reactor performance at time t. Further cell sorting, 16S rRNA gene sequencing, and correlation analysis partly attributed this accurate prediction to HNA genera (e.g., Anaerovibrio and unclassified Bacteroidales) and LNA genera (e.g., Achromobacter, Ochrobactrum, and unclassified Anaerolineae). In summary, our findings suggest that HNA and LNA cell routine enumeration, along with the trained model, can derive a fast approach to predict the AnMBR performance.

42 ENGINEERING↗