Jumbo phages protect their genomes from DNA-sensing bacterial defense systems by enclosing them within vesicles and nucleus-like compartments. Very little is known about defense systems specialized to counter these phages. Here, we show that AVAST Type 5 (Avs5) systems, part of the STAND superfamily and spanning three phylogenetic Avs5 clades, confer conserved immunity against jumbo phages. Using localization microscopy and biotin proximity labeling we demonstrate that Avs5 localizes to early infection vesicles, where it senses an essential, early expressed
phage protein named JADA—Jumbophage AVAST5 Defense Activator. Recognition of phage infection triggers the Sir2-like effector domain of Avs5 across all three Avs5 clades, resulting in rapid NAD+ hydrolysis, disruption of phage nucleus formation, and arrest of infection. These findings reveal a spatially coordinated bacterial immune strategy that targets an early vulnerability in jumbo phage infection.

Bacterial cells organize their genomes into a compact hierarchical structure called the nucleoid. Studying the nucleoid in cells faces challenges because of the cellular complexity while in vitro assays have difficulty in handling the fragile megabase-scale DNA biopolymers that make up bacterial genomes. Here, we introduce a method that overcomes these limitations as we develop and use a microfluidic device for the sequential extraction, purification, and analysis of bacterial nucleoids in individual microchambers. Our approach avoids any transfer or pipetting of the fragile megabase-size genomes and thereby prevents their fragmentation. We show how the microfluidic system can be used to extract and analyze single chromosomes from B. subtilis cells. Upon on-chip lysis, the bacterial genome expands in size and DNA-binding proteins are flushed away. Subsequently, exogeneous proteins can be added to the trapped DNA via diffusion. We envision that integrated microfluidic platforms will become an essential tool for the bottom-up assembly of complex biomolecular systems such as artificial chromosomes.

Microorganisms encoding for the N2O reductase (NosZ) are the only known biological sink of the potent greenhouse gas N2O and are central to global N2O mitigation efforts. Clade II NosZ populations are of particular biotechnological interest as they usually feature high N2O affinities and often lack other denitrification genes. We focus on the yet-unresolved ecological constraints selecting for different N2O-reducers strains and controlling the assembly of N2O-respiring communities. Two planktonic N2O-respiring mixed cultures were enriched at low dilution rates under limiting and excess dissolved N2O availability to assess the impact of substrate affinity and N2O cytotoxicity, respectively. Genome-resolved metaproteomics was used to infer the metabolism of the enriched populations. Under N2O limitation, clade II N2O-reducers fully outcompeted clade I affiliates, a scenario previously only theorized based on pure-cultures. All enriched N2O-reducers encoded and expressed the sole clade II NosZ, while also possessing other denitrification genes. Two Azonexus and Thauera genera affiliates dominated the culture, and we hypothesize their coexistence to be explained by the genome-inferred metabolic exchange of cobalamin intermediates. Under excess N2O, clade I and II populations coexisted; yet, proteomic evidence suggests that clade II affiliates respired most of the N2O, de facto outcompeting clade I affiliates. The single dominant N2O-reducer (genus Azonexus) notably expressed most cobalamin biosynthesis marker genes, likely to contrast the continuous cobalamin inactivation by dissolved cytotoxic N2O concentrations (400 μM). Ultimately, our results strongly suggest the solids dilution rate to play a pivotal role in controlling the selection among NosZ clades, albeit the conditions selecting for genomes possessing the sole nosZ remain elusive. We furthermore highlight the potential significance of N2O-cobalamin interactions in shaping the composition of N2O-respiring microbiomes.

Identifying structural proteins within the extracellular polymeric substances (EPS) will provide a better understanding of the stability of aerobic granular sludge (AGS) and biofilms in general. In this work, an abundant surface protein was identified and localized in the extracellular matrix of seawater-adapted AGS. Granules with good phosphate removal were cultivated in a sequencing batch bubble column reactor with acetate as a carbon source dissolved in seawater. “Candidatus Accumulibacter” was observed as the most dominant community member through fluorescent in-situ hybridization. A surface protein of 74.5 kDa was identified in the EPS extract of the seawater-adapted AGS by SDS-PAGE and mass spectrometry. The surface protein was produced by an Accumulibacter species and showed homology to S-layer proteins. A type 1 secretion system was found adjacent to the gene encoding for the surface protein, suggesting a possible export system. Antibodies generated from a unique peptide of the surface protein confirmed the extracellular location of the surface protein. Microscopy observations with antibody staining showed the surface protein forms dense structures within the Accumulibacter microcolonies and larger fiber structures around the microcolonies. These observations highlight the importance of the protein for the structural properties of the granule. To detect more structural proteins in the EPS, optimization of the EPS extraction and in situ imaging validation methods are essential.

Monosaccharides play a central role in metabolic networks and in the biosynthesis of glycomolecules, which perform essential functions across all domains of life. Thus, identifying and quantifying these building blocks is crucial in both research and industry. Routine methods have been established to facilitate the analysis of common monosaccharides. However, despite the presence of common metabolites, most organisms utilize distinct sets of monosaccharides and derivatives. These molecules therefore display a large diversity, potentially numbering in the hundreds or thousands, with many still unknown. This complexity presents significant challenges in the study of glycomolecules, particularly in microbes, including pathogens and those with the potential to serve as novel model organisms. This review discusses mass spectrometric techniques for the isomer-sensitive analysis of monosaccharides, their derivatives, and activated forms. Although mass spectrometry allows for untargeted analysis and sensitive detection in complex matrices, the presence of stereoisomers and extensive modifications necessitates the integration of advanced chromatographic, electrophoretic, ion mobility, or ion spectroscopic methods. Furthermore, stable-isotope incorporation studies are critical in elucidating biosynthetic routes in novel organisms.

The immense microbial diversity on Earth represents a vast genomic resource, yet discovering novel enzymes from complex environments remains challenging. Here, we combine a microbial enrichment with metagenomics and metaproteomics to facilitate the identification of microbial glycoside hydrolases that operate under defined conditions. We enriched microbial communities on the carbohydrate polymer pullulan at elevated temperatures under acidic conditions. Pullulan is a natural polysaccharide composed of maltotriose units linked by α-1,6-glycosidic bonds. Pullulan, along with its hydrolyzing enzymes, has broad applications across various industries. The enrichment inocula were sampled from thermophilic compost and from soil from the bank of a pond. In both cases, Alicyclobacillus was identified as the dominant microorganism. Metaproteomic analysis of the enriched biomass and secretome enabled the identification of several pullulan-degrading enzyme candidates from this organism. These enzymes were absent in the metagenomic analysis of the initial inoculum, which is highly complex with a wide diversity of species. This underscores the effectiveness of combining microbial enrichment with multi-omics for uncovering novel enzymes and sequence variants that operate under defined conditions from complex microbial environments.

Nitrous oxide (N2O) is the third most important greenhouse gas and originates primarily from natural and engineered microbiomes. Effective emission mitigations are currently hindered by the largely unresolved ecophysiological controls of coexisting N2O-converting metabolisms in complex communities. To address this, we used biological wastewater treatment as a model ecosystem and combined long-term metagenome-resolved metaproteomics with ex situ kinetic and full-scale operational characterization over nearly 2 years. By leveraging the evidence independently obtained at multiple ecophysiological levels, from individual genetic potential to actual metabolism and emergent community phenotype, the cascade of environmental and operational triggers driving seasonal N2O emissions has ultimately been resolved. We identified nitrifier denitrification as the dominant N2O-producing pathway and dissolved O2 as the prime operational parameter, paving the way to the design and fostering of robust emission control strategies. This work exemplifies the untapped potential of multi-meta-omics in the mechanistic understanding and ecological engineering of microbiomes towards reducing anthropogenic impacts and advancing sustainable biotechnological developments.

One Health seeks to integrate and balance the health of humans, animals, and environmental systems, which are intricately linked through microbiomes. These microbial communities exchange microbes and genes, influencing not only human and animal health but also key environmental, agricultural, and biotechnological processes. Preventing the emergence of pathogens as well as monitoring and controlling the composition of microbiomes through microbial effectors including virulence factors, toxins, antibiotics, non-ribosomal peptides, and viruses holds transformative potential. However, the mechanisms by which these microbial effectors shape microbiomes and their broader functional consequences for host and ecosystem health remain poorly understood. Metaproteomics offers a novel methodological framework as it provides insights into microbial dynamics by quantifying microbial biomass composition, metabolic functions, and detecting effectors like viruses, antimicrobial resistance proteins, and non-ribosomal peptides. Here, we highlight the potential of metaproteomics in elucidating microbial effectors and their impact on microbiomes and discuss their potential for modulating microbiomes to foster desired functions.

Enzymes are attractive catalysts due to their high chemo-, regio-, and enantioselectivity. In recent years, the application of enzymes in organic synthesis has expanded dramatically, especially for the synthesis of chiral alcohols and amines, two very important functional groups found in many active pharmaceutical ingredients (APIs). Indeed, many elegant routes employing such compounds have been described by industry. Yet, for the synthesis of chiral thiols and thioethers, likewise found in APIs albeit less ubiquitous, only very few biocatalytic syntheses have been reported, and stereocontrol has proved challenging. Here, we apply ene-reductases (EREDs), whose ability to initiate and control chemically challenging radical chemistries has recently emerged, to the synthesis of chiral thioethers from α-bromoacetophenones and pro-chiral vinyl sulfides, without requiring light. Depending on the choice of ERED either enantiomer of the product could be accessed. The highest conversion and selectivity were achieved with GluER T36A using fluorinated substrates, reaching up to 82% conversion and >99.5% ee. With α-bromoacetophenone and α-(methylthio)styrene, the reaction could be performed on a 100 mg scale, affording the product in a 46% isolated yield with a 93% ee. Finally, mechanistic studies were carried out using stopped-flow spectroscopy and protein mass spectrometry, providing insight into the preference of the enzyme for the intermolecular reaction. This work paves the way for new routes for the synthesis of thioether-containing compounds.

The challenging task of designing biopharmaceutical downstream processes is initially to select the type of unit operations, followed by optimizing their operating conditions. For complex flowsheet optimizations, the strategy becomes crucial in terms of duration and outcome. In this study, we compared three optimization strategies, namely, simultaneous, top-to-bottom, and superstructure decomposition. Moreover, all strategies were evaluated by either using chromatographic Mechanistic Models (MMs) or Artificial Neural Networks (ANNs). An overall evaluation of 39 flowsheets was performed, including a buffer-exchange step between the chromatography operations. All strategies identified orthogonal structures to be optimal, and the weighted overall performance values were generally consistent between the MMs and ANNs. In terms of time-efficiency, the decomposition method with MMs stands out when utilizing multiple cores on a multiprocessing system for simulations. This study analyses the influence of different optimization strategies on flowsheet optimization and advices on suitable strategies and modeling techniques for specific scenarios.

Methane removal is an essential step in drinking water production from methane-rich groundwaters. Conventional aeration-based stripping results in significant direct methane emissions, contributing up to one-third of a treatment plant's total carbon footprint. To address this, a full-scale trickling filter was operated for biological methane oxidation upstream of a submerged sand filter, and its performance was compared to a conventional aeration–submerged sand filtration set-up. Full-scale data were combined with ex-situ batch assays and metagenome-resolved metaproteomics to quantify the individual contribution of the main (a)biotic processes and characterize the enriched microbial communities. Both treatment setups fully removed methane, iron, ammonium, and manganese, yet the underlying mechanisms differed significantly. Methane was completely removed from the effluent after trickling filtration, with stripping and biological oxidation each accounting for half of the removal, thereby halving overall methane emissions. Methane-oxidizing bacteria not only outcompeted nitrifiers in the trickling filter, but also likely contributed directly to ammonia oxidation. In contrast to the submerged filter preceded by methane stripping, signatures of biological iron oxidation were almost completely absent in the trickling filter, suggesting that the presence of methane directly or indirectly promotes chemical iron oxidation. All systems had similar ex-situ manganese oxidation capacities, yet removal occurred only in the submerged filters but not the trickling filter. Ultimately, our results demonstrate that trickling filtration is effective in promoting biological methane oxidation at comparable produced drinking water quality, highlighting its potential for advancing sustainable drinking water production.

Extracellular proteins are supposed to play crucial roles in the formation and structure of biofilms and aggregates. However, often little is known about these proteins, in particular for microbial communities. Here, we use two advanced metaproteomic approaches to study the extracellular proteome in a granular Candidatus Accumulibacter enrichment as a proxy for microbial communities that form solid microbial granules, such as those used in biological wastewater treatment. Limited proteolysis of whole granules and metaproteome isolation from the culture's supernatant successfully classified over 50% of the identified protein biomass to be secreted. Moreover, structural and sequence-based classification identified 387 proteins, corresponding to over 50% of the secreted protein biomass, with characteristics that could aid the formation of aggregates, including filamentous, beta-barrel containing, and cell surface proteins. While various of these aggregate-forming proteins originated from Ca. Accumulibacter, some proteins associated with other taxa. This suggests that not only a range of different proteins but also multiple organisms contribute to granular biofilm formation. Therefore, the obtained extracellular metaproteome data from the granular Ca. Accumulibacter enrichment provides a resource for exploring proteins that potentially support the formation and stability of granular biofilms, whereas the demonstrated approaches can be applied to explore biofilms of microbial communities in general.

Nitrous oxide (N₂O) is a potent greenhouse gas of primarily microbial origin. Oxic and anoxic emissions are commonly ascribed to autotrophic nitrification and heterotrophic denitrification, respectively. Beyond this established dichotomy, we quantitatively show that heterotrophic denitrification can significantly contribute to aerobic nitrogen turnover and N₂O emissions in complex microbiomes exposed to frequent oxic/anoxic transitions. Two planktonic, nitrification-inhibited enrichment cultures were established under continuous organic carbon and nitrate feeding, and cyclic oxygen availability. Over a third of the influent organic substrate was respired with nitrate as electron acceptor at high oxygen concentrations (>6.5 mg/L). N₂O accounted for up to one-quarter of the nitrate reduced under oxic conditions. The enriched microorganisms maintained a constitutive abundance of denitrifying enzymes due to the oxic/anoxic frequencies exceeding their protein turnover—a common scenario in natural and engineered ecosystems. The aerobic denitrification rates are ascribed primarily to the residual activity of anaerobically synthesised enzymes. From an ecological perspective, the selection of organisms capable of sustaining significant denitrifying activity during aeration shows their competitive advantage over other heterotrophs under varying oxygen availabilities. Ultimately, we propose that the contribution of heterotrophic denitrification to aerobic nitrogen turnover and N₂O emissions is currently underestimated in dynamic environments.

Shower systems provide unique environments that are conducive to biofilm formation and the proliferation of pathogens. The water heating temperature is a delicate decision that can impact microbial growth, balancing safety and energy consumption. This study investigated the impact of different heating temperatures (39 °C, 45 °C, 51 °C and 58 °C) on the shower hose biofilm (exposed to a final water temperature of 39 °C) using controlled full-scale shower setups. Whole metagenome sequencing and metaproteomics were employed to unveil the microbial composition and protein expression profiles. Overall, the genes and enzymes associated with disinfectant resistance and biofilm formation appeared largely unaffected. However, metagenomic analysis revealed a sharp decline in the number of total (86,371 to 34,550) and unique genes (32,279 to 137) with the increase in hot water temperature, indicating a significant reduction of overall microbial complexity. None of the unique proteins were detected in the proteomics experiments, suggesting smaller variation among biofilms on the proteome level compared to genomic data. Furthermore, out of 43 pathogens detected by metagenomics, only 5 could actually be detected by metaproteomics. Most interestingly, our study indicates that 45 °C heating temperature may represent an optimal balance. It minimizes active biomass (ATP) and reduces the presence of pathogens while saving heating energy. Our study offered new insights into the impact of heating temperature on shower hose biofilm formation and proposed optimal parameters that ensure biosafety while conserving energy.

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis

Purification of recombinantly produced biopharmaceuticals involves removal of host cell material, such as host cell proteins (HCPs). For lysates of the common expression host Escherichia coli (E. coli) over 1500 unique proteins can be identified. Currently, understanding the behavior of individual HCPs for purification operations, such as preparative chromatography, is limited. Therefore, we aim to elucidate the elution behavior of individual HCPs from E. coli strain BLR(DE3) during chromatography. Understanding this complex mixture and knowing the chromatographic behavior of each individual HCP improves the ability for rational purification process design. Specifically, linear gradient experiments were performed using ion exchange (IEX) and hydrophobic interaction chromatography, coupled with mass spectrometry-based proteomics to map the retention of individual HCPs. We combined knowledge of protein location, function, and interaction available in literature to identify trends in elution behavior. Additionally, quantitative structure–property relationship models were trained relating the protein 3D structure to elution behavior during IEX. For the complete data set a model with a cross-validated R2 of 0.55 was constructed, that could be improved to a R2 of 0.70 by considering only monomeric proteins. Ultimately this study is a significant step toward greater process understanding.

The thermoalkaliphile Caldalkalibacillus thermarum possesses a highly branched respiratory chain. These primarily facilitate growth at a wide range of dissolved oxygen levels. The aim of this study was to investigate the regulation of C. thermarum respiratory chain. C. thermarum was cultivated in chemostat bioreactors with a range of oxygen levels (0.25% O2–4.2% O2). Proteomic analysis unexpectedly showed that both the type I and the type II NADH dehydrogenase present are constitutive. The two terminal oxidases detected were the cytochrome c:oxygen aa3 oxidase, whose abundance was highest at 4.2% O2. The cytochrome c:oxygen ba3 oxidase was more abundant at most other O2 levels, but its abundance started to decline below 0.42% O2. We expected this would result in the emergence of the cytochrome c:oxygen bb3 complex or the menaquinol:oxygen bd complex, the other two terminal oxidases of C. thermarum; but neither was detected. Furthermore, the sodium-proton antiporter complex Mrp was downregulated under the lower oxygen levels. Normally, in alkaliphiles, this enzyme is considered crucial for sodium homeostasis. We propose that the existence of a sodium:acetate exporter decreases the requirement for Mrp under strong oxygen limitation.

Mechanistic models mostly focus on the target protein and some selected process- or product-related impurities. For a better process understanding, however, it is advantageous to describe also reoccurring host cell protein impurities. Within the purification of biopharmaceuticals, the binding of host cell proteins to a chromatographic resin is far from being described comprehensively. For a broader coverage of the binding characteristics, large-scale proteomic data and systems level knowledge on protein interactions are key. However, a method for determining binding parameters of the entire host cell proteome to selected chromatography resins is still lacking. In this work, we have developed a method to determine binding parameters of all detected individual host cell proteins in an Escherichia coli harvest sample from large-scale proteomics experiments. The developed method was demonstrated to model abundant and problematic proteins, which are crucial impurities to be removed. For these 15 proteins covering varying concentration ranges, the model predicts the independently measured retention time during the validation gradient well. Finally, we optimized the anion exchange chromatography capture step in silico using the determined isotherm parameters of the persistent host cell protein contaminants. From these results, strategies can be developed to separate abundant and problematic impurities from the target antigen.

The Craspase CRISPR-Cas effector consists of the RNA-guided ribonuclease gRAMP and the protease TPR-CHAT, coupling target RNA recognition to protease activation. The natural substrate of Craspase is Csx30, a protein cleaved in two fragments that subsequently activates downstream antiviral pathways. Here, we determined the protease substrate specificity of Craspase from Candidatus “Jettenia caeni” (Jc-Craspase). We find that Jc-Craspase cleaves Jc-Csx30 in a target RNA-dependent fashion in A|S, which is different from the sites found in two other studied Craspases (L|D and M|K for Candidatus “Scalindua brodae” and Desulfonema ishimotonii, respectively). The fact that Craspase cleaves a nonconserved site across orthologs indicates the evolution of specific protein interactions between Craspase and its respective Csx30 target protein. The Craspase family thus represents a panel of proteases with different substrate specificities, which we exploited for the development of a readout for multiplexed RNA detection.