About

Manuel Kleiner is an Associate Professor in the Department of Plant and Microbial Biology at North Carolina State University. His research focuses on microbial communities that are ubiquitous in all environments supporting life, emphasizing their roles in global biogeochemical cycles, plant and animal health, and biotechnological processes. Kleiner develops and employs cultivation-independent methods such as metagenomics, metaproteomics, and metabolomics, alongside targeted approaches like enzyme assays, single-cell imaging, and stable isotope experiments, to study the metabolism, physiology, and evolutionary ecology of microbial symbioses and uncultured microorganisms. His projects include investigating factors that govern energy efficiency in bacteria, the role of horizontal gene transfer in bacterial metabolic evolution, and developing advanced methods for microbial community analysis. Kleiner's work aims to deepen understanding of microbial interactions in the soil-plant interface, particularly within the rhizosphere, to enhance crop resilience and sustainability. His research is supported by grants such as the Decoding the Rhizobiota Interactome for improved Crop Resilience and InRoot, which focus on microbial interactions, plant-microbe relationships, and their implications for agriculture and environmental sustainability.

Research topics

• Biology
• Genetics
• Computational biology
• Data Mining
• Computer Science
• Ecology
• Microbiology
• Bioinformatics
• Agronomy
• Biotechnology

Selected publications

• Area under the curve quantification outperforms spectral counting in metaproteomics, but matching between runs is detrimental

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-06

  articleOpen access

  Abstract Metaproteomics enables the functional characterization of microbiomes and host-microbe interactions by detecting and quantifying thousands of proteins. In data-dependent acquisition metaproteomics, protein quantification is commonly performed using either MS1-based area under the curve (AUC) or MS2-based peptide spectral counts (SpC). In AUC quantification, match between runs (MBR) is frequently employed to minimize data sparsity, yet its impact on metaproteomic data remains unclear. Understanding MBR’s impact on metaproteomics data is especially important due to the high peak density in the MS1 mass spectra and the potential presence of not only proteins, but even entire organisms, in one sample and their absence in the other, which would complicate accurate feature mapping and transfer. While accurate quantification is essential for deriving meaningful biological inferences from metaproteomic analyses, systematic evaluations of AUC and SpC quantification in metaproteomics remain scarce. In this study, we used defined complex metaproteomic samples to perform a ground truth-based evaluation of AUC and SpC quantification and to determine the impact of MBR on AUC quantification. We found that MBR led to a substantial number of falsely identified proteins in complex samples. Protein identifications from an organism not present in the sample were wrongly transferred from other samples when MBR was used. We found that MBR-free AUC data had a wider dynamic range, higher quantitative accuracy, and more sensitive detection of abundance differences. Significance of the Study Although metaproteomics is increasingly used to advance microbiome research, quantification strategies in metaproteomics are mostly selected based on convention rather than evidence, due to a lack of ground truth-based evaluation of quantification strategies in metaproteomics. Accurate protein quantification is key to deriving meaningful biological inferences from metaproteomic samples, yet it remains challenging due to their high complexity and uneven protein abundances. Here, we used defined metaproteomic samples to evaluate widely used quantification strategies in metaproteomics and to determine the effects of match between runs (MBR) on quantitative accuracy. Based on our findings, MBR adds falsely identified proteins to metaproteomic data. While MBR-free AUC offers a broader dynamic range and higher quantitative accuracy, SpC offers better proteome coverage. With this study, we provide an evidence-based framework for the informed selection of quantification strategies in metaproteomics, and highlight the strengths and limitations of these approaches with respect to proteome coverage, dynamic range, quantitative accuracy, and error propagation. Our findings also have important implications for the biological interpretation of data derived from these strategies and lay the groundwork for future studies validating quantitative approaches in data-independent acquisition workflows.

  PublisherOA PDFDOI

• Assembly and use of a plant gnotobiotic growth system for plant–microbe interaction studies in cereals

  DRYAD · 2026-03-18

  datasetOpen accessSenior author

  The development of microbial-based agricultural amendments that work consistently in the field requires an understanding of the molecular mechanisms of plant–microbe interactions. Studying these underlying mechanisms of interaction demands the ability to grow plants under environmentally controlled and gnotobiotic conditions (i.e. all microorganisms interacting with the plant are known, whether that is germ-free, defined microbial communities, or natural communities). The currently available plant gnotobiotic systems are not suitable to study large plants of agricultural relevance such as cereals. Moreover, most of these systems lack the ability to manage irrigation. Here we introduce GNOVA, a new gnotobiotic system designed to accommodate cereal plants with the ability to manage irrigation. This new system is an accessible platform composed of a 3D printed base and commercially available materials. This protocol provides a step-by-step guide to assembling the system and experiment set up. Furthermore, we present a performance comparison of GNOVA to a gnotobiotic bag system. GNOVA extended plant growth from two weeks in the bag system up to 17 weeks for wheat and 4 weeks for maize. The germination rate of both crops also increased within GNOVA from 66% to 100% for wheat and from 75% to 100% for maize. Wheat grown within GNOVA developed tillers, which were absent in plants of the same age within the bag system. The fresh weight of maize grown in the GNOVA was 594% higher than in the bag system. Additionally, the shoot height and root length of maize were 89% and 57% greater within the GNOVA system than in the bags, respectively. The GNOVA system extends the toolbox available to scientists for the exploration of plant–microbiota interactions beyond the seedling stage in cereals by providing increased growth space and irrigation management.

  PublisherDOI

• Assessing the diversity and functional profile of the “microbial proteome” in fermented foods

  Food & Function · 2026-01-01

  articleOpen accessSenior author

  Fermented foods contain a large amount and diversity of microbial proteins which contribute to their nutritional profile.

  PublisherOA PDFDOI

• Metagenomics-enabled proteomics reveals how AMF and PSB co-inoculation reshapes tomato rhizosphere dynamics across growth stages

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-13

  articleOpen access

  Urban agriculture increasingly relies on compost-based substrates for sustainable production, yet we lack a clear characterization of how these systems respond to biological amendments aimed at introducing beneficial microbiota. Here we investigated how developmental stage and co-inoculation with arbuscular mycorrhizal fungi (AMF) and phosphate-solubilizing bacteria (PSB) reshape rhizosphere microbial function in Solanum lycopersicum grown in compost-based urban farm substrate. Using plant physiology assays, 16S rRNA amplicon sequencing, and metagenome-informed metaproteomics, we characterized tomato physiological responses and rhizosphere microbial activity during flowering and fruiting across control, single AMF, single PSB, and AMF and PSB co-inoculation treatments. Co-inoculation synergistically enriched beneficial taxa, improved fruit nutrient accumulation, elevated nutrient transporter and quorum sensing protein production, and drove stress-driven dormancy in competitively excluded taxa, with responses varying between developmental stages. Our findings establish metagenome-informed metaproteomics as essential for resolving stage-specific rhizosphere microbiome functional responses to tomato development and AMF and PSB co-inoculation.

  PublisherDOI

• TrIdent - An R package to automate transductomics analysis of virus-like particle mediated DNA mobilization

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-01

  articleOpen accessSenior author

  Background: Transduction is a form of horizontal gene transfer in which bacterial DNA is packaged and transferred by virus-like particles (VLPs). Transductomics is a sequencing-based method used to detect DNA carried by VLPs. During transductomics analysis, reads from a sample's ultra-purified VLPs are mapped to metagenomic contigs assembled from the same sample's whole-community. The read mapping produces coverage patterns that require a time-consuming manual inspection and classification process which makes the method's use unfeasible for datasets with many samples. Results: ification), that uses pattern-matching to automate the transductomics data analysis and that is available as an R package (https://jlmaier12.github.io/TrIdent/). There is no software equivalent to TrIdent so we compared TrIdent's classifications of transductomics datasets to classifications made by human classifiers. TrIdent's classifications were generally comparable to the manual classifications on a previously generated, manually classified transductomics dataset. When applied to newly generated transductomics data from the murine microbiota, TrIdent agreed with two independent human classifiers as much as the two independent human classifications agreed with each other. TrIdent classified transductomics datasets in a fraction of the time needed by human classifiers, and the classifications produced by TrIdent are fully reproducible. We used TrIdent to explore three murine gut transductomes and found that bacterial DNA associated with the Oscillospiraceae and Turicibacteraceae families was highly enriched in the DNA packaged by VLPs as compared to the whole community metagenomes. Conclusions: The TrIdent software is a more accessible, more efficient, and more reproducible alternative to the manual inspection of read coverage patterns previously required for transductomics data analysis. To demonstrate the application of TrIdent, we analyzed transductomics datasets from murine fecal pellets and showed that specific low abundance bacterial families appear to be heavily involved in transduction.

  PublisherOA PDFDOI

• Mouse gut microbiome pre- and post- perturbation (assemblies and MAGs)

  DRYAD · 2026-02-20

  datasetOpen accessSenior author

  Assemblies and MAGs generated from conventional mouse fecal pellets collected pre- and post- gut microbiome perturbation.

  PublisherDOI

• The Metaproteomics Initiative: Five Years of Community-Driven Progress

  ChemRxiv · 2026-02-23

  articleOpen access

  The Metaproteomics Initiative was officially launched in 2021 to strengthen collaboration, promote knowledge exchange, and support and lead standardization efforts within the growing metaproteomics community. Over the past five years, the Initiative has developed into a structured, global network of researchers. It has launched community-driven benchmark studies, helped shape emerging metadata and reporting standards, developed practical guidance and training materials, organized international symposia, and fostered connections across the microbiome research landscape (https://metaproteomics.org/). We outline the Initiative's organization, activities, achievements, and ongoing efforts, and reflect on how sustained, community-led coordination has shaped the development of metaproteomics as a field. We further position the Grand Metaproteome Challenges as a next step toward coordinated, community-scale biological research, aimed at advancing functional microbiome studies across clinical, industrial, and environmental application domains, and invite engagement from the wider microbiome and omics communities.

  PublisherDOI

• A Minimal Medium for Culturing Maize Root–Associated Microbes Based on a Plant Growth Medium

  Phytobiomes Journal · 2026-01-15 · 1 citations

  articleOpen accessSenior author

  Plant-associated microbiota play a critical role in host resilience to both abiotic and biotic stresses. However, understanding the underlying mechanisms of interaction within these communities, as well as between these communities and their hosts, remains challenging because of the complexity and dynamic nature of plant-associated microbiota. Synthetic microbial communities can serve as experimentally tractable models to establish a fundamental understanding of plant–microbiota interactions. Here, we report the development of a defined minimal growth medium for a well-characterized seven-member maize root synthetic microbial community. The medium is based on a standard plant-growth medium, Murashige and Skoog, to enable its use for both in vitro and in planta studies. Using genome-scale metabolic modeling and auxotrophy prediction, we identified amino acid and vitamin requirements of each of the seven species and, based on these predictions, added arginine; proline; serine; asparagine; leucine; isoleucine; lysine; cysteine; glutamine; and vitamins B2, B3, B5, B6, B7, and B12 to support bacterial growth. This minimal medium enables controlled investigation of microbial physiology, metabolite exchange, and community interactions, and lays the foundation for scalable in vitro and in planta experiments, facilitating future research on plant microbiome functions. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

  PublisherOA PDFDOI

• Genome-scale community metabolic modeling of maize root-associated microbiota shows that root exudates stimulate diverse metabolic interactions

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-15

  articleOpen accessSenior author

  ABSTRACT Microbes play a vital role in plant development, health, and resilience, yet relatively little is known about the specific metabolic mechanisms driving interactions in these host-associated communities. Systems biology models enable a computational approach to understanding metabolic interactions, which can be difficult to pinpoint experimentally; however, these methods cannot yet accommodate the large number of species in natural communities. Synthetic communities (SynComs) provide a more tractable alternative to explore targeted interactions. Here, we investigated metabolite exchange in a seven-member maize root-associated SynCom, specifically accounting for plant host context by designing a customized exudate medium. We constructed metabolic models for each bacterial species and curated them with in vitro phenotyping data to reflect experimentally based carbon uptake potential. Flux balance analysis of individual species demonstrated that integrating phenotype data and changing medium type had substantial impacts on predicted growth rates, which in turn shaped potential interspecies interactions. In silico community growth optimization of the seven-member community model showed that the exudate medium supported a more diverse community composition compared to minimal medium, with predictions of community member abundance closely aligned to literature-derived experimental results. Predicted metabolite exchange in the root exudate environment showed Enterobacter ludwigii as a community hub, and cross-feeding of indole suggested a potential effect of bacterial community interactions on the plant host. Our in silico findings indicate the host plays an important role in structuring microbial interactions and cross-feeding at the metabolic level, underscoring the importance of considering environmental context from both theoretical and experimental perspectives. IMPORTANCE True understanding of a system is marked by the ability to predict its behavior. The complexity of natural host-microbe systems represents a frontier of knowledge that scientists are working to understand, and elucidating principles of interactions within multi-partite microbial communities remains a challenge in microbial ecology. Synthetic communities provide a tractable starting point for investigating interaction mechanisms, and computational approaches complement laboratory experiments by systematically evaluating multiple possibilities for metabolic pathway processing, thereby allowing us to comprehensively study the interconnected metabolic networks of host-associated microbiota. The model we developed for the seven-member maize root-associated bacterial community presents a step toward predicting plant-microbe behavior, providing hypotheses for future experimental testing and serving as a template for expanding model complexity to more members and other systems.

  PublisherDOI

• The ecology, evolution, and physiology of Cardinium: a widespread heritable endosymbiont of invertebrates

  Iowa State University Digital Repository (Iowa State University) · 2025-07-24

  articleOpen access

  Candidatus Cardinium hertigii (Cardinium) are maternally transmitted obligate intracellular bacteria found in a wide range of invertebrate hosts, including arthropods and nematodes. Infection with Cardinium has substantial consequences for host biology, with many strains manipulating host reproduction to favor symbiont transmission by (i) feminizing male hosts, (ii) altering host sex allocation, (iii) inducing parthenogenesis, or (iv) causing cytoplasmic incompatibility. Other Cardinium strains can confer benefits to their host or alter host behavior. Cardinium-modified host phenotypes can result in selective sweeps of cytological elements through host populations and potentially reinforce host speciation. Cardinium has potential for applications in controlling arthropod pest species and arthropod-vectored disease transmission, although much remains to be explored regarding Cardinium physiology and host interactions. In this review, we provide an overview of Cardinium evolution and host distribution. We describe the various host phenotypes associated with Cardinium and how biological and environmental factors influence these symbioses. We also provide an overview of Cardinium metabolism, physiology, and potential mechanisms for interactions with hosts based on recent studies using genomics and transcriptomics. Finally, we discuss new methodologies and directions for Cardinium research, including improving our understanding of Cardinium physiology, response to environmental stress, and potential for controlling arthropod pest populations.

  Publisher

Recent grants

• Metaproteomics to investigate intestinal microbiota-host and -diet interactions

  NIH · $1.9M · 2020–2026

• Collaborative Research: The saboteur's tools: mechanisms for host reproductive manipulation by the bacterial arthropod endosymbiont Cardinium hertigii

  NSF · $440k · 2020–2024

Frequent coauthors

• Nicole Dubilier

  Max Planck Institute for Marine Microbiology

  82 shared

• Tjorven Hinzke

  Universität Greifswald

  58 shared

• Harald R. Gruber‐Vodicka

  Kiel University

  37 shared

• Manuel Liebeke

  Kiel University

  36 shared

• Thomas Schweder

  Institute of Marine Biotechnology

  29 shared

• Stephanie Markert

  Universität Greifswald

  26 shared

• Cecilia Wentrup

  Max Planck Institute for Marine Microbiology

  26 shared

• Marc Strous

  University of Calgary

  20 shared

Labs

• Kleiner LabPI