Biology subjects

Hinzke, T.

Publications and source records attributed to Hinzke, T..

10 recordsLinked to original sources

bioRxiv2026

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

Metaproteomics enables the functional characterization of complex microbial communities by detecting and quantifying thousands of proteins. Accurate quantification is essential for deriving meaningful biological inferences from metaproteomes. In mass spectrometry-driven metaproteomics, protein quantification is performed using either MS1-based area under the curve (AUC) or MS2-based peptide spectral counts (SpC). Systematic benchmarking of AUC vs. SpC quantification for metaproteomics, however, is lacking. Additionally, the impact of matching identifications between runs (MBR) on AUC quantification accuracy has not been evaluated. Here, we tested whether AUC or SpC is better suited for quantification in metaproteomics using data-dependent acquisition mass spectrometry data and investigated the impact of MBR on AUC using defined metaproteomics samples with known composition as ground truth. We found that MBR incorrectly transferred peptide and protein identifications and led to a substantial number of falsely identified proteins in samples of known composition. Additionally, when comparing MBR-free AUC data to SpC, AUC data had a wider dynamic range, higher quantitative accuracy, and higher sensitivity for detecting abundance differences. Based on these findings, we recommend MBR-free AUC quantification for metaproteomics analysis, while SpC-based identifications can be used to increase the number of identified proteins to obtain a more comprehensive view of expressed functions. Significance of the studyAlthough accurate quantification of proteins is crucial for characterizing microbial functions in microbiomes, quantification strategies in metaproteomics are mostly selected based on convention rather than evidence. With this study, we provide an evidence-based framework for the informed selection of quantification strategies in metaproteomics. We highlight the strengths and limitations of the tested approaches with respect to dynamic range, quantitative accuracy, and proteome coverage. Based on our results, we recommend using AUC data without MBR for quantitative metaproteomics.

molecular biology↗

bioRxiv2025

RNA virus genomes from centuries- to millennia-old Adelie penguin mummies

Direct studies of long-term RNA virus evolution are largely limited to chemically-fixed specimens from museums collected over the past two centuries. Detecting genomic traces of RNA viruses in older, buried remains is considered highly unlikely. The cold, dry conditions of Antarctica may represent an exception. Here, natural mummification of penguins and seals--animals that form large colonies where RNA viruses circulate--is common, potentially facilitating RNA virus genome recovery. Here, we show that Adelie penguin (Pygoscelis adeliae) mummies, ranging in age from recent to nearly two millennia, indeed contain ancient viral genome fragments. Metatranscriptomic analyses yielded near-complete genome sequences of a picornavirus (Megrivirus epengu) and a rotavirus D (Rotavirus deltagastroenteritidis) from relatively recent specimens. We further retrieved rotavirus D sequences from a 280-year-old individual and a near-complete rotavirus G (Rotavirus gammagastroenteritidis) genome from a 2000-year-old one. These findings pave the way to direct studies of RNA virus evolution across millennia.

molecular biology↗

bioRxiv2025

Evaluation of statistical approaches for differential metaproteomics

BackgroundMetaproteomics characterizes and compares molecular phenotypes of organisms in communities by comprehensively analyzing their protein expression profiles using statistical methods. However, not all statistical methods are suitable for determining differentially abundant protein groups in metaproteomic analyses. Statistical challenges in metaproteomics include: data sparsity, non-normality, compositionality, and large between-sample variability. These challenges can potentially be addressed with several data processing steps, including imputation, normalization, transformation, and selection of the appropriate statistical tests. The potential combinations of different processing methods create a complex matrix of analysis options and it is currently unclear how these combinations impact the results of statistical tests on metaproteomic data. ResultsTo determine what data processing methods and statistical tests are best for identifying differentially abundant proteins in metaproteomics datasets, we generated a set of thirteen metaproteomic samples with known compositions, known differences, and differing levels of complexity. These defined metaproteomes address the general challenges outlined above, using various scenarios in metaproteomic data analyses. We compared over 110 different statistical analysis combination options, including regression-based tools, general statistics inference, and machine learning techniques. We found that several combinations within the frameworks of limma, edgeR, MaAslin2, custom linear and Bayesian linear models, and random forests all offer suitable evaluation options. ConclusionsWe highlight key recommendations for differential expression analysis in metaproteomics. Our work enables improved assessment of statistical methods for metaproteomics by establishing a framework for testing statistical approaches, including comprehensive raw mass spectrometry data and reproducible benchmarking code.

molecular biology↗

bioRxiv2024

Transformation of the drug ibuprofen by Priestia megaterium: Reversible glycosylation and generation of hydroxylated metabolites

As one of the most-consumed drugs worldwide, ibuprofen (IBU) reaches the environment in considerable amounts as environmental pollutant, necessitating studies of its further biotransformation as potential removal mechanism. Therefore, we screened bacteria with known capabilities to degrade aromatic environmental pollutants, belonging to the genera Bacillus, Priestia (formerly also Bacillus) Paenibacillus, Mycobacterium, and Cupriavidus, for their ability to transform ibuprofen. We identified five transformation products, namely 2-hydroxyibuprofen, carboxyibuprofen, ibuprofen pyranoside, 2-hydroxyibuprofen pyranoside, and 4-carboxy--methylbenzene-acetic acid. Based on our screening results, we focused on ibuprofen biotransformation by Priestia megaterium SBUG 518 with regard to structure of transformation products and bacterial physiology. Biotransformation reactions by P. megaterium involved (A) the hydroxylation of the isobutyl side chain at two positions, and (B) conjugate formation via esterification with a sugar molecule of the carboxylic group of ibuprofen and an ibuprofen hydroxylation product. Glycosylation seems to be a detoxification process, since the ibuprofen conjugate (ibuprofen pyranoside) was considerably less toxic than the parent compound to P. megaterium SBUG 518. Based on proteome profile changes and inhibition assays, cytochrome P450 systems are likely crucial for ibuprofen transformation in P. megaterium SBUG 518. The toxic effect of ibuprofen appears to be caused by interference of the drug with different physiological pathways, including especially sporulation, as well as amino acid and fatty acid metabolism. ImportanceIbuprofen is a highly consumed drug, and, as it reaches the environment in high quantities, also an environmental pollutant. It is therefore of great interest how microorganisms transform this drug and react to it. Here, we screened several bacteria for their ability to transform ibuprofen. Priestia megaterium SBUG 518 emerged as highly capable and was therefore studied in greater detail. We show that P. megaterium transforms ibuprofen via two main pathways, hydrolyzation and reversible conjugation. These pathways bear resemblance to those in humans. Ibuprofen likely impacts the physiology of P. megaterium on several levels, including spore formation. Taken together, P. megaterium SBUG 518 is well suited as a model organism to study bacterial ibuprofen metabolism.

microbiology↗

bioRxiv2023

Metaproteogenomics resolution of a high-CO2 aquifer community suggests an active symbiotic lifestyle of groundwater Gracilibacteria

BackgroundBacteria of the Candidate Phyla Radiation (CPR), constituting about 25% of the bacterial biodiversity, are characterized by small cell size and patchy genomes without complete key metabolic pathways, suggesting a symbiotic lifestyle. Gracilibacteria (BD1-5), which are part of the CPR branch, possess alternate coded genomes and have not yet been cultivated. However, besides genomic evidence, little is known about the lifestyle of Gracilibacteria, their temporal dynamics, and activity in natural ecosystems, particularly in groundwater, where they were initially been genomically resolved. Therefore, we here aimed to investigate Gracilibacteria activity in situ and to discern expressed genes involved in their lifestyle, using the metaproteogenome of Gracilibacteria as a function of time in the cold-water geyser Wallender Born in the Volcanic Eifel region in Germany. ResultsWe coupled genome-resolved metagenomics and metaproteomics to investigate a cold-water geyser microbial community enriched in Gracilibacteria across a 12-day time-series. Groundwater was collected and sequentially filtered to fraction CPR and other bacteria. Based on 670 Gbps of metagenomic data, 1129 different ribosomal protein S3 marker genes and 751 high-quality genomes (123 population genomes after dereplication), we identified dominant bacteria belonging to Galionellales and Gracilibacteria along with keystone microbes, which were low in genomic abundance but substantially contributing to proteomic abundance. Seven high-quality Gracilibacteria genomes showed typical limitations, such as limited amino acid or nucleotide synthesis, in their central metabolism but no co-occurrence with potential hosts. The genomes of these Gracilibacteria encoded for a high number of proteins related to a symbiotic or even predatory lifestyle, e.g., type IV and type II secretion system subunits and features related to cell-cell interactions and cell motility, which were also detected on protein level. ConclusionsCoupling metagenomics to metaproteomics enabled us to identify microbial keystone taxa in a high-CO2 aquifer, and to reveal microbial dynamics of Gracilibacteria. We posit that Gracilibacteria might be successful microbial predators in this ecosystem, potentially aiding in population control of this highly perturbed microbial geyser community from the deep biosphere.

ecology↗

bioRxiv2020

Metabolic differences between symbiont subpopulations in the deep-sea tubeworm Riftia pachyptila

The hydrothermal vent tube worm Riftia pachyptila lives in intimate symbiosis with intracellular sulfur-oxidizing gammaproteobacteria. Although the symbiont population consists of a single 16S rRNA phylotype, bacteria in the same host animal exhibit a remarkable degree of metabolic diversity: They simultaneously utilize two carbon fixation pathways and various energy sources and electron acceptors. Whether these multiple metabolic routes are employed in the same symbiont cells, or rather in distinct symbiont subpopulations, was unclear. As Riftia symbionts vary considerably in cell size and shape, we enriched individual symbiont cell sizes by density gradient centrifugation in order to test whether symbiont cells of different sizes show different metabolic profiles. Metaproteomic analysis and statistical evaluation using clustering and random forests, supported by microscopy and flow cytometry, strongly suggest that Riftia symbiont cells of different sizes represent metabolically dissimilar stages of a physiological differentiation process: Small symbionts actively divide and may establish cellular symbiont-host interaction, as indicated by highest abundance of the cell division key protein FtsZ and highly abundant chaperones and porins in this initial phase. Large symbionts, on the other hand, apparently do not divide, but still replicate DNA, leading to DNA endoreduplication. Highest abundance of enzymes for CO2 fixation, carbon storage and biosynthesis in large symbionts indicates that in this late differentiation stage the symbionts metabolism is efficiently geared towards the production of organic material. We propose that this division of labor between smaller and larger symbionts benefits the productivity of the symbiosis as a whole.

microbiology↗

bioRxiv2019

Host-microbe interactions in the chemosynthetic Riftia pachyptila symbiosis

The deep-sea tubeworm Riftia pachyptila lacks a digestive system, but completely relies on bacterial endosymbionts for nutrition. Although the symbiont has been studied in detail on the molecular level, such analyses were unavailable for the animal host, because sequence information was lacking. To identify host-symbiont interaction mechanisms, we therefore sequenced the Riftia transcriptome, which enabled comparative metaproteomic analyses of symbiont-containing versus symbiont-free tissues, both under energy-rich and energy-limited conditions. We demonstrate that metabolic interactions include nutrient allocation from symbiont to host by symbiont digestion, and substrate transfer to the symbiont by abundant host proteins. Our analysis further suggests that Riftia maintains its symbiont by protecting the bacteria from oxidative damage, while also exerting symbiont population control. Eukaryote-like symbiont proteins might facilitate intracellular symbiont persistence. Energy limitation apparently leads to reduced symbiont biomass and increased symbiont digestion. Our study provides unprecedented insights into host-microbe interactions that shape this highly efficient symbiosis.

systems biology↗

bioRxiv2019

The Trichoplax microbiome: the simplest animal lives in an intimate symbiosis with two intracellular bacteria

Summary paragraphPlacozoa is an enigmatic phylum of simple, microscopic, marine metazoans. Although intracellular bacteria have been found in all members of this phylum, almost nothing is known about their identity, location and interactions with their host. We used metagenomic and metatranscriptomic sequencing of single host individuals, plus metaproteomic and imaging analyses, to show that the placozoan Trichoplax H2 lives in symbiosis with two intracellular bacteria. One symbiont forms a new genus in the Midichloriaceae (Rickettsiales) and has a genomic repertoire similar to that of rickettsial parasites, but does not appear to express key genes for energy parasitism. Correlative microscopy and 3-D electron tomography revealed that this symbiont resides in an unusual location, the rough endoplasmic reticulum of its hosts internal fiber cells. The second symbiont belongs to the Margulisbacteria, a phylum without cultured representatives and not known to form intracellular associations. This symbiont lives in the ventral epithelial cells of Trichoplax, likely metabolizes algal lipids digested by its host, and has the capacity to supplement the placozoans nutrition. Our study shows that even the simplest animals known have evolved highly specific and intimate associations with symbiotic, intracellular bacteria, and highlights that symbioses with microorganisms are a basal trait of animal life.

microbiology↗

bioRxiv2018

Horizontal acquisition of a patchwork Calvin cycle by symbiotic and free-living Campylobacterota (formerly Epsilonproteobacteria)

Although the majority of known autotrophs use the Calvin-Benson-Bassham (CBB) cycle for carbon fixation, all currently described autotrophs from the Campylobacterota (previously Epsilonproteobacteria) use the reductive tricarboxylic acid cycle (rTCA) instead. We discovered campylobacterotal epibionts (\"Candidatus Thiobarba\") of deep-sea mussels that have acquired a complete CBB cycle and lost key genes of the rTCA cycle. Intriguingly, the phylogenies of campylobacterotal CBB genes suggest they were acquired in multiple transfers from Gammaproteobacteria closely related to sulfur-oxidizing endosymbionts associated with the mussels, as well as from Betaproteobacteria. We hypothesize that \"Ca. Thiobarba\" switched from the rTCA to a fully functional CBB cycle during its evolution, by acquiring genes from multiple sources, including co-occurring symbionts. We also found key CBB cycle genes in free-living Campylobacterota, suggesting that the CBB cycle may be more widespread in this phylum than previously known. Metatranscriptomics and metaproteomics confirmed high expression of CBB cycle genes in mussel-associated \"Ca. Thiobarba\". Direct stable isotope fingerprinting showed that \"Ca. Thiobarba\" has typical CBB signatures, additional evidence that it uses this cycle for carbon fixation. Our discovery calls into question current assumptions about the distribution of carbon fixation pathways across the tree of life, and the interpretation of stable isotope measurements in the environment.

microbiology↗

bioRxiv2018

A metaproteomics method to determine carbon sources and assimilation pathways of species in microbial communities

Measurements of the carbon stable isotope ratio ({delta}13C) are widely used in biology to address major questions regarding food sources and metabolic pathways used by organisms. Measurement of these so called stable carbon isotope fingerprints (SIFs) for microbes involved in biogeochemical cycling and microbiota of plants and animals have led to major discoveries in environmental microbiology. Currently, obtaining SIFs for microbial communities is challenging as the available methods either only provide limited taxonomic resolution, such as with the use of lipid biomarkers, or are limited in throughput, such as NanoSIMS imaging of single cells.\n\nHere we present \"direct Protein-SIF\" and the Calis-p software package (https://sourceforge.net/projects/calis-p/), which enable high-throughput measurements of accurate {delta}13C values for individual species within a microbial community. We benchmark the method using 20 pure culture microorganisms and show that the method reproducibly provides SIF values consistent with gold standard bulk measurements performed with an isotope ratio mass spectrometer. Using mock community samples, we show that SIF values can also be obtained for individual species within a microbial community. Finally, a case study of an obligate bacteria-animal symbiosis showed that direct Protein-SIF confirms previous physiological hypotheses and can provide unexpected new insights into the symbionts metabolism. This confirms the usefulness of this new approach to accurately determine {delta}13C values for different species in microbial community samples.\n\nSignificanceTo understand the roles that microorganisms play in diverse environments such as the open ocean and the human intestinal tract, we need an understanding of their metabolism and physiology. A variety of methods such as metagenomics and metaproteomics exist to assess the metabolism of environmental microorganisms based on gene content and gene expression. These methods often only provide indirect evidence for which substrates are used by a microorganism in a community. The direct Protein-SIF method that we developed allows linking microbial species in communities to the environmental carbon sources they consume by determining their stable carbon isotope signature. Direct Protein-SIF also allows assessing which carbon fixation pathway is used by autotrophic microorganisms that directly assimilate CO2.

microbiology↗