Determination of bacterial cell dry mass by transmission electron microscopy and densitometric image analysis

Application of propionate-producing bacterial consortium in ruminal methanogenesis inhibited environment with bromoethanesulfonate as a methanogen direct inhibitor

Methane production in ruminants is primarily due to the conversion of metabolic hydrogen (H2), produced during anaerobic microbial fermentation, into methane by ruminal methanogens. While this process plays a crucial role in efficiently disposes of H2, it also contributes to environmental pollution and eliminating methane production in the rumen has proven to be challenging. This study investigates the use of probiotics, specifically propionate-producing bacteria, to redirect accumulated H2 in a methane-mitigated environment. For this objective, we supplemented experimental groups with Lactiplantibacillus plantarum and Megasphaera elsdenii for the reinforced acrylate pathway (RA) and Selenomonas ruminantium and Acidipropionibacterium thoenii for the reinforced succinate pathway (RS), as well as a consortium of all four strains (CB), with the total microbial concentration at 1.0 × 1010 cells/mL. To create a methane-mitigated environment, 2-bromoethanesulfonate (BES) was added to all experimental groups at a dose of 15 mg/0.5 g of feed. BES reduced methane production by 85% in vitro, and the addition of propionate-producing bacteria with BES further decreased methane emission by up to 94% compared with the control (CON) group. Although BES did not affect the alpha diversity of the ruminal bacteriome, it reduced total volatile fatty acid production and altered beta diversity of ruminal bacteriota, indicating microbial metabolic adaptations to H2 accumulation. Despite using different bacterial strains targeting divergent metabolic pathways (RA and RS), a decrease in the dominance of the [Eubacterium] ruminantium group suggesting that both approaches may have a similar modulatory effect. An increase in the relative abundance of Succiniclasticum in the CB group suggests that propionate metabolism is enhanced by the addition of a propionate-producing bacterial consortium. These findings recommend using a consortium of propionate-producing bacteria to manage H2 accumulation by altering the rumen bacteriome, thus mitigating the negative effects of methane reduction strategies.

Why biofouling cannot contribute to the vertical transport of small microplastic

In contrast to expectations, even buoyant microplastics like polyethylene and polypropylene are found at high concentrations in deep sediment traps and deep-sea sediments. To explain the presence of such buoyant microplastic particles at great ocean depths, several vertical transport mechanisms are under discussion with biofouling as one of the most referred. Biofouling is thought to increase the density of microplastic particles to the point that they sink to the deep sea, but this has mostly been shown on large microplastic particles ≥ 1 mm. However, although microplastics are defined as particles between 1 and 5000 μm, most microplastics are < 100 μm. In the ocean plastic particles continuously fragment, converting each "large" particle into several "small" particles, and particle abundance increases drastically with decreasing size. We argue that biofouling is not a reasonable transport mechanism for small microplastic particles ≤ 100 μm, which form the majority of microplastics. Biofilm density depends on its community and composition. A biofilm matrix of extracellular polymeric substances and bacteria has a lower density than seawater, in contrast to diatoms or large organisms like mussels or barnacles. We suggest that a small microplastic particle cannot host a biofilm community consisting of the heavy organisms required to induce sinking. Furthermore, to reach the deep sea within a reasonable timespan, a microplastic particle needs to sink several meters per day. Therefore, the excess density has to not only exceed that of seawater, but also be large enough to enable rapid sinking. We thus argue that biofouling cannot be an efficient vertical transport mechanism for small microplastic. However, biofouling of small microplastic may promote the likelihood of its incorporation into sinking marine snow and increase the probability of its ingestion, allowing its transport to depth.

Metaproteomic analysis decodes trophic interactions of microorganisms in the dark ocean

Proteins in the open ocean represent a significant source of organic matter, and their profiles reflect the metabolic activities of marine microorganisms. Here, by analyzing metaproteomic samples collected from the Pacific, Atlantic and Southern Ocean, we reveal size-fractionated patterns of the structure and function of the marine microbiota protein pool in the water column, particularly in the dark ocean (>200 m). Zooplankton proteins contributed three times more than algal proteins to the deep-sea community metaproteome. Gammaproteobacteria exhibited high metabolic activity in the deep-sea, contributing up to 30% of bacterial proteins. Close virus-host interactions of this taxon might explain the dominance of gammaproteobacterial proteins in the dissolved fraction. A high urease expression in nitrifiers suggested links between their dark carbon fixation and zooplankton urea production. In summary, our results uncover the taxonomic contribution of the microbiota to the oceanic protein pool, revealing protein fluxes from particles to the dissolved organic matter pool.

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm. This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

Glycogen phase separation drives macromolecular rearrangement and asymmetric division in E. coli

Bacteria often experience nutrient limitation in nature and the laboratory. While exponential and stationary growth phases are well characterized in the model bacterium Escherichia coli, little is known about what transpires inside individual cells during the transition between these two phases. Through quantitative cell imaging, we found that the position of nucleoids and cell division sites becomes increasingly asymmetric during transition phase. These asymmetries were coupled with spatial reorganization of proteins, ribosomes, and RNAs to nucleoid-centric localizations. Results from live-cell imaging experiments, complemented with genetic and 13C whole-cell nuclear magnetic resonance spectroscopy studies, show that preferential accumulation of the storage polymer glycogen at the old cell pole leads to the observed rearrangements and asymmetric divisions. In vitro experiments suggest that these phenotypes are likely due to the propensity of glycogen to phase separate in crowded environments, as glycogen condensates exclude fluorescent proteins under physiological crowding conditions. Glycogen-associated differences in cell sizes between strains and future daughter cells suggest that glycogen phase separation allows cells to store large glucose reserves without counting them as cytoplasmic space.

Airborne survival and stress response in Listeria monocytogenes across different growth temperatures

In the food industry, ensuring food safety during transportation and storage is vital, with temperature regulation preventing spoilage. However, airborne contamination through foodborne pathogens remains a concern. Listeria monocytogenes, a psychrotolerant foodborne pathogen, has been linked to various foodborne outbreaks. Therefore, understanding how its airborne characteristics depend on the growth temperature is imperative. As a result, when the L. monocytogenes was floated in air for 30 and 60 min, the surviving population of 15 °C-grown L. monocytogenes that was suspended in air and attached on the surface was significantly higher than L. monocytogenes grown at 25°C and 37 °C. The fatty acid analysis revealed a significantly higher proportion of shorter chain fatty acids in L. monocytogenes grown at 15 °C compared to those grown at 37 °C. Under aerosolization, L. monocytogenes encountered osmotic and cold stresses regardless of their growth temperature. Transcriptomic analysis showed that stress response related genes, such as oxidative and cold stress response, as well as PTS system related genes were upregulated at 15 °C, resulting in the enhanced resistance to various stresses during aerosolization. These results provide insights into the different responses of aerosolized L. monocytogenes according to the different growth temperatures, highlighting a critical factor in preventing airborne cross-contamination.

Optimization of periodic treatment strategies for bacterial biofilms using an agent-based in silico approach

Biofilms are responsible for most chronic infections and are highly resistant to antibiotic treatments. Previous studies have demonstrated that periodic dosing of antibiotics can help sensitize persistent subpopulations and reduce the overall dosage required for treatment. Because the dynamics and mechanisms of biofilm growth and the formation of persister cells are diverse and are affected by environmental conditions, it remains a challenge to design optimal periodic dosing regimens. Here, we develop a computational agent-based model to streamline this process and determine key parameters for effective treatment. We used our model to test a broad range of persistence switching dynamics and found that if periodic antibiotic dosing was tuned to biofilm dynamics, the dose required for effective treatment could be reduced by nearly 77%. The biofilm architecture and its response to antibiotics were found to depend on the dynamics of persister cells. Despite some differences in the response of biofilm governed by different persister switching rates, we found that a general optimized periodic treatment was still effective in significantly reducing the required antibiotic dose. As persistence becomes better quantified and understood, our model has the potential to act as a foundation for more effective strategies to target bacterial infections.

How to identify cell material in a single ice grain emitted from Enceladus or Europa

Icy moons like Enceladus, and perhaps Europa, emit material sourced from their subsurface oceans into space via plumes of ice grains and gas. Both moons are prime targets for astrobiology investigations. Cassini measurements revealed a large compositional diversity of emitted ice grains with only 1 to 4% of Enceladus's plume ice grains containing organic material in high concentrations. Here, we report experiments simulating mass spectra of ice grains containing one bacterial cell, or fractions thereof, as encountered by advanced instruments on board future space missions to Enceladus or Europa, such as the SUrface Dust Analyzer onboard NASA's upcoming Europa Clipper mission at flyby speeds of 4 to 6 kilometers per second. Mass spectral signals characteristic of the bacteria are shown to be clearly identifiable by future missions, even if an ice grain contains much less than one cell. Our results demonstrate the advantage of analyses of individual ice grains compared to a diluted bulk sample in a heterogeneous plume.

Introducing bacterial community turnover times to elucidate temporal and spatial hotspots of biological instability in a large Austrian drinking water distribution network

Ensuring biological stability in drinking water distribution systems (DWDSs) is important to reduce the risk of aesthetic, operational and hygienic impairments of the distributed water. Drinking water after treatment often changes in quality during transport due to interactions with pipe-associated biofilms, temperature increases and disinfectant residual decay leading to potential biological instability. To comprehensively assess the potential for biological instability in a large chlorinated DWDS, a tool-box of bacterial biomass and activity parameters was applied, introducing bacterial community turnover times (BaCTT) as a direct, sensitive and easy-to-interpret quantitative parameter based on the combination of 3H-leucine incorporation with bacterial biomass. Using BaCTT, hotspots and periods of bacterial growth and potential biological instability could be identified in the DWDS that is fed by water with high bacterial growth potential. A de-coupling of biomass from activity parameters was observed, suggesting that bacterial biomass parameters depict seasonally fluctuating raw water quality rather than processes related to biological stability of the finished water in the DWDS. BaCTT, on the other hand, were significantly correlated to water age, disinfectant residual, temperature and a seasonal factor, indicating a higher potential of biological instability at more distant sampling sites and later in the year. As demonstrated, BaCTT is suggested as a novel, sensitive and very useful parameter for assessing the biological instability potential. However, additional studies in other DWDSs are needed to investigate the general applicability of BaCTT depending on water source, applied treatment processes, biofilm growth potential on different pipe materials, or size, age and complexity of the DWDS.

Slow closure of Earth's carbon cycle

Carbon near the Earth's surface cycles between the production and consumption of organic carbon; the former sequesters carbon dioxide while the latter releases it. Microbes attempt to close the loop, but the longer organic matter survives, the slower microbial degradation becomes. This aging effect leaves observable quantitative signatures: Organic matter decays at rates that are inversely proportional to its age, while microbial populations and concentrations of organic carbon in ocean sediments decrease at distinct powers of age. Yet mechanisms that predict this collective organization remain unknown. Here, I show that these and other observations follow from the assumption that the decay of organic matter is limited by progressively rare extreme fluctuations in the energy available to microbes for decomposition. The theory successfully predicts not only observed scaling exponents but also a previously unobserved scaling regime that emerges when microbes subsist on the minimum energy flux required for survival. The resulting picture suggests that the carbon cycle's age-dependent dynamics are analogous to the slow approach to equilibrium in disordered systems. The impact of these slow dynamics is profound: They preclude complete oxidation of organic carbon in sediments, thereby freeing molecular oxygen to accumulate in the atmosphere.

Spatial structure, chemotaxis and quorum sensing shape bacterial biomass accumulation in complex porous media

Biological tissues, sediments, or engineered systems are spatially structured media with a tortuous and porous structure that host the flow of fluids. Such complex environments can influence the spatial and temporal colonization patterns of bacteria by controlling the transport of individual bacterial cells, the availability of resources, and the distribution of chemical signals for communication. Yet, due to the multi-scale structure of these complex systems, it is hard to assess how different biotic and abiotic properties work together to control the accumulation of bacterial biomass. Here, we explore how flow-mediated interactions allow the gut commensal Escherichia coli to colonize a porous structure that is composed of heterogenous dead-end pores (DEPs) and connecting percolating channels, i.e. transmitting pores (TPs), mimicking the structured surface of mammalian guts. We find that in presence of flow, gradients of the quorum sensing (QS) signaling molecule autoinducer-2 (AI-2) promote E. coli chemotactic accumulation in the DEPs. In this crowded environment, the combination of growth and cell-to-cell collision favors the development of suspended bacterial aggregates. This results in hot-spots of resource consumption, which, upon resource limitation, triggers the mechanical evasion of biomass from nutrients and oxygen depleted DEPs. Our findings demonstrate that microscale medium structure and complex flow coupled with bacterial quorum sensing and chemotaxis control the heterogenous accumulation of bacterial biomass in a spatially structured environment, such as villi and crypts in the gut or in tortuous pores within soil and filters.

The yielding behaviour of human mucus

Mucus is a viscoelastic material with non-linear rheological properties such as a yield stress of the order of a few hundreds of millipascals to a few tens of pascals, due to a complex network of mucins in water along with non-mucin proteins, DNA and cell debris. In this review, we discuss the origin of the yield stress in human mucus, the changes in the rheology of mucus with the occurrence of diseases, and possible clinical applications in disease detection as well as cure. We delve into the domain of mucus rheology, examining both macro- and microrheology. Macrorheology involves investigations conducted at larger length scales (∼ a few hundreds of μm or higher) using traditional rheometers, which probe properties on a bulk scale. It is significant in elucidating various mucosal functions within the human body. This includes rejecting unwanted irritants out of lungs through mucociliary and cough clearance, protecting the stomach wall from the acidic environment as well as biological entities, safeguarding cervical canal from infections and providing a swimming medium for sperms. Additionally, we explore microrheology, which encompasses studies performed at length scales ranging from a few tens of nm to a μm. These microscale studies find various applications, including the context of drug delivery. Finally, we employ scaling analysis to elucidate a few examples in lung, cervical, and gastric mucus, including settling of irritants in lung mucus, yielding of lung mucus in cough clearance and cilial beating, spreading of exogenous surfactants over yielding mucus, swimming of Helicobacter pylori through gastric mucus, and lining of protective mucus in the stomach. The scaling analyses employed on the applications mentioned above provide us with a deeper understanding of the link between the rheology and the physiology of mucus.

Microbial gas fermentation technology for sustainable food protein production

The development of novel, sustainable, and robust food production technologies represents one of the major pillars to address the most significant challenges humanity is going to face on earth in the upcoming decades - climate change, population growth, and resource depletion. The implementation of microfoods, i.e., foods formulated with ingredients from microbial cultivation, into the food supply chain has a huge potential to contribute towards energy-efficient and nutritious food manufacturing and represents a means to sustainably feed a growing world population. This review recapitulates and assesses the current state in the establishment and usage of gas fermenting bacteria as an innovative feedstock for protein production. In particular, we focus on the most promising representatives of this taxon: the hydrogen-oxidizing bacteria (hydrogenotrophs) and the methane-oxidizing bacteria (methanotrophs). These unicellular microorganisms can aerobically metabolize gaseous hydrogen and methane, respectively, to provide the required energy for building up cell material. A protein yield over 70% in the dry matter cell mass can be reached with no need for arable land and organic substrates making it a promising alternative to plant- and animal-based protein sources. We illuminate the holistic approach to incorporate protein extracts obtained from the cultivation of gas fermenting bacteria into microfoods. Herein, the fundamental properties of the bacteria, cultivation methods, downstream processing, and potential food applications are discussed. Moreover, this review covers existing and future challenges as well as sustainability aspects associated with the production of microbial protein through gas fermentation.

Single-cell mass distributions reveal simple rules for achieving steady-state growth

IMPORTANCE

Microbiologists have watched clear liquid turn cloudy for over 100 years. While the cloudiness of a culture is proportional to its total biomass, growth rates from optical density measurements are challenging to interpret when cells change size. Many bacteria adjust their size at different steady-state growth rates, but also when shifting between starvation and growth. Optical density cannot disentangle how mass is distributed among cells. Here, we use single-cell mass measurements to demonstrate that a population of cells in batch culture achieves a stable mass distribution for only a short period of time. Achieving steady-state growth in rich medium requires low initial biomass concentrations and enough time for individual cell mass accumulation and cell number increase via cell division to balance out. Steady-state growth is important for reliable cell mass distributions and experimental reproducibility. We discuss how mass variation outside of steady-state can impact physiology, ecology, and evolution experiments.

Dielectrophoresis microbial characterization and isolation of Staphylococcus aureus based on optimum crossover frequency

Characterization of antibiotic-resistant bacteria is a significant concern that persists for the rapid classification and analysis of the bacteria. A technology that utilizes the manipulation of antibiotic-resistant bacteria is key to solving the significant threat of these pathogenic bacteria by rapid characterization profile. Dielectrophoresis (DEP) can differentiate between antibiotic-resistant and susceptible bacteria based on their physical structure and polarization properties. In this work, the DEP response of two Gram-positive bacteria, namely, Methicillin-resistant Staphylococcus aureus (MRSA) and Methicillin-susceptible S. aureus (MSSA), was investigated and simulated. The DEP characterization was experimentally observed on the bacteria influenced by oxacillin and vancomycin antibiotics. MSSA control without antibiotics has crossover frequencies (f x 0 ${f_{x0}}$ ) from 6 to 8 MHz, whereas MRSA control is from 2 to 3 MHz. Thef x 0 ${f_{x0}}$ changed when bacteria were exposed to the antibiotic. As for MSSA, thef x 0 ${f_{x0}}$ decreased to 3.35 MHz compared tof x 0 ${f_{x0}}$ MSSA control without antibiotics, MRSA,f x 0 ${f_{x0}}$ increased to 7 MHz when compared to MRSA control. The changes in the DEP response of MSSA and MRSA with and without antibiotics were theoretically proven using MyDEP and COMSOL simulation and experimentally based on the modification to the bacteria cell walls. Thus, the DEP response can be employed as a label-free detectable method to sense and differentiate between resistant and susceptible strains with different antibiotic profiles. The developed method can be implemented on a single platform to analyze and identify bacteria for rapid, scalable, and accurate characterization.

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general 'interaction' models have been formulated, but what is currently lacking are models that link monoculture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment. We measure population growth under single substrate competition or with double species-specific substrates (substrate 'indifference'), and starting from varying cell ratios of either species. Using experimental data as input, we first consider a mean-field model of resource-based competition, which captures well the empirically observed growth rates for monocultures, but fails to correctly predict growth rates in co-culture mixtures, in particular for skewed starting species ratios. Based on this, we extend the model by cross-feeding interactions where the consumption of substrate by one consumer produces metabolites that in turn are resources for the other consumer, thus leading to positive feedback in the species system. Two different cross-feeding options were considered, which either lead to constant metabolite cross-feeding, or to a regulated form, where metabolite utilization is activated with rates according to either a threshold or a Hill function, dependent on metabolite concentration. Both mathematical proof and experimental data indicate regulated cross-feeding to be the preferred model to constant metabolite utilization, with best co-culture growth predictions in case of high Hill coefficients, close to binary (on/off) activation states. This suggests that species use the appearing metabolite concentrations only when they are becoming high enough; possibly as a consequence of their lower energetic content than the primary substrate. Metabolite sharing was particularly relevant at unbalanced starting cell ratios, causing the minority partner to proliferate more than expected from the competitive substrate because of metabolite release from the majority partner. This effect thus likely quells immediate substrate competition and may be important in natural communities with typical very skewed relative taxa abundances and slower-growing taxa. In conclusion, the regulated bacterial interaction network correctly describes species substrate growth reactions in mixtures with few kinetic parameters that can be obtained from monoculture growth experiments.

A Morphometric Approach to Understand Prokaryoplankton: A Study in the Sicily Channel (Central Mediterranean Sea)

A new understanding of plankton ecology has been obtained by studying the phenotypic traits of free-living prokaryotes in the Sicily Channel (Central Mediterranean Sea), an area characterised by oligotrophic conditions. During three cruises carried out in July 2012, January 2013 and July 2013, the volume and morphology of prokaryotic cells were assessed microscopically using image analysis in relation to environmental conditions. The study found significant differences in cell morphologies among cruises. The largest cell volumes were observed in the July 2012 cruise (0.170 ± 0.156 µm³), and the smallest in the January 2013 cruise (0.060 ± 0.052 µm³). Cell volume was negatively limited by nutrients and positively by salinity. Seven cellular morphotypes were observed among which cocci, rods and coccobacilli were the most abundant. Cocci, although they prevailed numerically, always showed the smallest volumes. Elongated shapes were positively related to temperature. Relationships between cell morphologies and environmental drivers indicated a bottom-up control of the prokaryotic community. The morphology/morphometry-based approach is a useful tool for studying the prokaryotic community in microbial ecology and should be widely applied to marine microbial populations in nature.

Processing and Physicochemical Properties of Magnetite Nanoparticles Coated with Curcuma longa L. Extract

In this work, Curcuma longa L. extract has been used in the synthesis and direct coating of magnetite (Fe₃O₄) nanoparticles ~12 nm, providing a surface layer of polyphenol groups (-OH and -COOH). This contributes to the development of nanocarriers and triggers different bio-applications. Curcuma longa L. is part of the ginger family (Zingiberaceae); the extracts of this plant contain a polyphenol structure compound, and it has an affinity to be linked to Fe ions. The nanoparticles' magnetization obtained corresponded to close hysteresis loop M_s = 8.81 emu/g, coercive field H_c = 26.67 Oe, and low remanence energy as iron oxide superparamagnetic nanoparticles (SPIONs). Furthermore, the synthesized nanoparticles (G-M@T) showed tunable single magnetic domain interactions with uniaxial anisotropy as addressable cores at 90-180°. Surface analysis revealed characteristic peaks of Fe 2p, O 1s, and C 1s. From the last one, it was possible to obtain the C-O, C=O, -OH bonds, achieving an acceptable connection with the HepG2 cell line. The G-M@T nanoparticles do not induce cell toxicity in human peripheral blood mononuclear cells or HepG2 cells in vitro, but they can increase the mitochondrial and lysosomal activity in HepG2 cells, probably related to an apoptotic cell death induction or to a stress response due to the high concentration of iron within the cell.

Rapid antimicrobial susceptibility testing for low bacterial concentrations integrating a centrifuge based bacterial cell concentrator

Antibiotic resistance threatens human health worldwide. Patients infected with antibiotic-resistant bacteria require appropriate antibiotic prescriptions based on a rapid antibiotic susceptibility test (AST). Various rapid AST methods have been developed to replace the conventional AST method, which requires a long testing time. However, in most cases, these methods require a high density of bacterial samples, which leads to an additional incubation or concentration process. In this study, we introduce a rapid AST platform that allows the use of low-density bacterial samples by concentrating bacterial cells and performing AST on a single microfluidic chip. In addition, the outlet-free loading process enables the platform to load the sample and concentrate bacteria into a small field of view for single-cell detection. Using this method, rapid AST determined antibiotic resistance in three hours from a standard strain of 10³ colony-forming unit (CFU) per ml bacterial concentration. This technique can be used for the cell-based drug testing of various low-concentration bacterial samples.

Assessing the growth kinetics and stoichiometry of Escherichia coli at the single-cell level

Microfluidic cultivation and single-cell analysis are inherent parts of modern microbial biotechnology and microbiology. However, implementing biochemical engineering principles based on the kinetics and stoichiometry of growth in microscopic spaces remained unattained. We here present a novel integrated framework that utilizes distinct microfluidic cultivation technologies and single-cell analytics to make the fundamental math of process-oriented biochemical engineering applicable at the single-cell level. A combination of non-invasive optical cell mass determination with sub-pg sensitivity, microfluidic perfusion cultivations for establishing physiological steady-states, and picoliter batch reactors, enabled the quantification of all physiological parameters relevant to approximate a material balance in microfluidic reaction environments. We determined state variables (biomass concentration based on single-cell dry weight and mass density), biomass synthesis rates, and substrate affinities of cells grown in microfluidic environments. Based on this data, we mathematically derived the specific kinetics of substrate uptake and growth stoichiometry in glucose-grown Escherichia coli with single-cell resolution. This framework may initiate microscale material balancing beyond the averaged values obtained from populations as a basis for integrating heterogeneous kinetic and stoichiometric single-cell data into generalized bioprocess models and descriptions.

Geobacter sulfurreducens' Unique Metabolism Results in Cells with a High Iron and Lipid Content

Geobacter sulfurreducens is a ubiquitous iron-reducing bacterium in soils, and in engineered systems, it can respire an electrode to produce measurable electric current. Its unique metabolism, heavily dependent on an extensive network of cytochromes, requires a unique cell composition. In this work, we used metallomics, cell fraction and elemental analyses, and transcriptomics to study and analyze the cell composition of G. sulfurreducens. Elemental composition studies (C, H, O, N, and ash content) showed high C:O and H:O ratios of approximately 1.7:1 and 0.25:1, indicative of more reduced cell composition that is consistent with high lipid content. Our study shows that G. sulfurreducens cells have a large amount of iron (2 ± 0.2 μg/g dry weight) and lipids (32 ± 0.5% dry weight/dry weight) and that this composition does not change whether the cells are grown with a soluble or an insoluble electron acceptor. The high iron concentration, higher than similar microorganisms, is attributed to the production of cytochromes that are abundant in transcriptomic analyses in both solid and soluble electron acceptor growth. The unique cell composition of G. sulfurreducens must be considered when growing this microorganism for lab studies and commercial applications. IMPORTANCE Geobacter sulfurreducens is an electroactive microorganism. In nature, it grows on metallic minerals by transferring electrons to them, effectively "breathing" metals. In a manmade system, it respires an electrode to produce an electric current. It has become a model organism for the study of electroactive organisms. There are potential biotechnological applications of an organism that can bridge the gap between biology and electrical signal and, as a ubiquitous iron reducer in soils around the world, G. sulfurreducens has an impact on the global iron cycle. We measured the concentrations of metals, macromolecules, and basic elements in G. sulfurreducens to define this organism's composition. We also used gene expression data to discuss which proteins those metals could be associated with. We found that G. sulfurreducens has a large amount of lipid and iron compared to other bacteria-these observations are important for future microbiologists and biotechnologists working with the organism.

A Biocatalytic Platform for the Synthesis of Enantiopure Propargylic Alcohols and Amines

Propargylic alcohols and amines are versatile building blocks in organic synthesis. We demonstrate a straightforward enzymatic cascade to synthesize enantiomerically pure propargylic alcohols and amines from readily available racemic starting materials. In the first step, the peroxygenase from Agrocybe aegerita converted the racemic propargylic alcohols into the corresponding ketones, which then were converted into the enantiomerically pure alcohols using the (R)-selective alcohol dehydrogenase from Lactobacillus kefir or the (S)-selective alcohol dehydrogenase from Thermoanaerobacter brokii. Moreover, an enzymatic Mitsunobu-type conversion of the racemic alcohols into enantiomerically enriched propargylic amines using (R)-selective amine transaminase from Aspergillus terreus or (S)-selective amine transaminase from Chromobacterium violaceum was established. The one-pot two-step cascade reaction yielded a broad range of enantioenriched alcohol and amine products in 70–99% yield.

In vivo characterization of electroactive biofilms inside porous electrodes with MR Imaging

Identifying the limiting processes of electroactive biofilms is key to improve the performance of bioelectrochemical systems (BES). For modelling and developing BES, spatial information of transport phenomena and biofilm distribution are required and can be determined by Magnetic Resonance Imaging (MRI) in vivo, in situ and in operando even inside opaque porous electrodes. A custom bioelectrochemical cell was designed that allows MRI measurements with a spatial resolution of 50 μm inside a 500 μm thick porous carbon electrode. The MRI data showed that only a fraction of the electrode pore space is colonized by the Shewanella oneidensis MR-1 biofilm. The maximum biofilm density was observed inside the porous electrode close to the electrode-medium interface. Inside the biofilm, mass transport by diffusion is lowered down to 45% compared to the bulk growth medium. The presented data and the methods can be used for detailed models of bioelectrochemical systems and for the design of improved electrode structures.

The use of magnetic resonance imaging can contribute to a better understanding of limiting processes occurring in electroactive biofilms especially inside opaque porous electrodes.

In vitro fermentation profiles of undigested fractions from legume and nut particles are affected by particle cohesion and entrapped macronutrients

Insoluble undigested food residues are the predominant dietary form of 'fibre' from food plants, with the potential for fermentation by microbial species resident within the large intestine. Here we present results on in vitro fermentation of undigested fractions of legumes (chickpea flour, lentil flour, mung bean flour), and nuts (peanut, almond, macadamia) using a pooled faecal inoculum from pigs fed a nut- and legume-free diet. All substrates were pre-digested in vitro. Nuts were also separated into two particle sizes (PS), cell cluster (CC = 710-1000 μm) and fine (F = 250-500 μm), to test the effect of PS. All substrates tested were fermented for 48 hours, and measured according to gas production, with lentil (within legume flours) being the highest gas producer, and peanut being the highest gas producer within nuts. Undigested fractions from Nuts_F had significantly higher gas production than those from Nuts_CC, consistent with differences in surface area between the two PS. Relative short chain fatty acid concentrations between samples as metabolite end-products were consistent with relative gas production. Analysis of unfermented residues after different fermentation times, showed that cellular integrity was a major factor controlling fermentation rates and that entrapped protein/starch (legumes) and lipid (nuts) all contributed to the fermentation outcomes.

Meteorites as Food Source on Early Earth: Growth, Selection, and Inhibition of a Microbial Community on a Carbonaceous Chondrite

Meteoritic material accumulated on the surface of the anoxic early Earth during the Late Heavy Bombardment around 4.0 Gya and may have provided Earth's surface with extraterrestrial nutrients and energy sources. This research investigates the growth of an anaerobic microbial community from pond sediment on native and pyrolyzed (heat-treated) carbonaceous chondrite Cold Bokkeveld. The community was grown anaerobically in liquid media. Native Cold Bokkeveld supported the growth of a phylogenetically clustered subset of the original pond community by habitat filtering. The anaerobic community on meteorite was dominated by the Deltaproteobacteria Geobacteraceae and Desulfuromonadaceae. Members of these taxa are known to use elemental sulfur and ferric iron as electron acceptors, and organic compounds as electron donors. Pyrolyzed Cold Bokkeveld, however, was inhibitory to the growth of the microbial community. These results show that carbonaceous chondrites can support and select for a specific anaerobic microbial community, but that pyrolysis, for example by geothermal activity, could inhibit microbial growth and toxify the material. This research shows that extraterrestrial meteoritic material can shape the abundance and composition of anaerobic microbial ecosystems with implications for early Earth. These results also provide a basis to design anaerobic material processing of asteroidal material for future human settlement.

Thickness and roughness of transparent gold-palladium anodes have no impact on growth kinetics and yield coefficients of early-stage Geobacter sulfurreducens biofilms

Geobacter sulfurreducens is the model organism for electroactive microorganisms performing direct extracellular electron transfer and forming thick mature biofilm electrodes. Although numerous physiological properties of mature biofilm electrodes are deciphered, there is an extensive gap of knowledge on the early-stage biofilm formation. We have shown recently that transparent gold-palladium (AuPd) electrodes allow for analysis of early-stage biofilm formation using confocal laser scanning microscopy. Here we analysed the influence of thickness (ranging from 12.5 to 200 nm) and roughness of AuPd electrodes on physiological parameters of G. sulfurreducens early-stage biofilms. We show that when grown potentiostatically at -200 mV vs. Ag/ AgCl sat. KCl neither maximum current density (jmax of ∼ 80-150 µA cm-2) nor lag time (lag t of ∼ 0.2-0.4 days) or single cell yield coefficients (YNe of 1.43 × 1012 cells mole--1) of the biofilms are influenced by the electrode preparation. This confirms the robustness of the experimental approach, which is an inevitable prerequisite for obtaining reliable results in follow-up experiments.

Defining Local Chemical Conditions in Magnetosomes of Magnetotactic Bacteria

Defining chemical properties of intracellular organelles is necessary to determine their function(s) as well as understand and mimic the reactions they host. However, the small size of bacterial and archaeal microorganisms often prevents defining local intracellular chemical conditions in a similar way to what has been established for eukaryotic organelles. This work proposes to use magnetite (Fe₃O₄) nanocrystals contained in magnetosome organelles of magnetotactic bacteria as reporters of elemental composition, pH, and redox potential of a hypothetical environment at the site of formation of intracellular magnetite. This methodology requires combining recent single-cell mass spectrometry measurements together with elemental composition of magnetite in trace and minor elements. It enables a quantitative characterization of chemical disequilibria of 30 chemical elements between the intracellular and external media of magnetotactic bacteria, revealing strong transfers of elements with active influx or efflux processes that translate into elemental accumulation (Mo, Se, and Sn) or depletion (Sr and Bi) in the bacterial internal medium of up to seven orders of magnitude relative to the extracellular medium. Using this concept, we show that chemical conditions in magnetosomes are compatible with a pH of 7.5-9.5 and a redox potential of -0.25 to -0.6 V.

Simultaneous Raman and infrared spectroscopy: a novel combination for studying bacterial infections at the single cell level

Sepsis is a life-threatening clinical condition responsible for approximately 11 million deaths worldwide. Rapid and accurate identification of pathogenic bacteria and its antimicrobial susceptibility play a critical role in reducing the morbidity and mortality rates related to sepsis. Raman and infrared spectroscopies have great potential to be used as diagnostic tools for rapid and culture-free detection of bacterial infections. Despite numerous reports using both methods to analyse bacterial samples, there is to date no study collecting both Raman and infrared signatures from clinical samples simultaneously due to instrument incompatibilities. Here, we report for the first time the use of an emerging technology that provides infrared signatures via optical photothermal infrared (O-PTIR) spectroscopy and Raman spectra simultaneously. We use this approach to analyse 12 bacterial clinical isolates including six isolates of Gram-negative and six Gram-positive bacteria commonly associated with bloodstream infection in humans. To benchmark the single cell spectra obtained by O-PTIR spectroscopy, infrared signatures were also collected from bulk samples via both FTIR and O-PTIR spectroscopies. Our findings showed significant similarity and high reproducibility in the infrared signatures obtained by all three approaches, including similar discrimination patterns when subjected to clustering algorithms. Principal component analysis (PCA) showed that O-PTIR and Raman data acquired simultaneously from bulk bacterial isolates displayed different clustering patterns due to the ability of both methods to probe metabolites produced by bacteria. By contrast, signatures of microbial pigments were identified in Raman spectra, providing complementary and orthogonal information compared to infrared, which may be advantageous as it has been demonstrated that certain pigments play an important role in bacterial virulence. We found that infrared spectroscopy showed higher sensitivity than Raman for the analysis of individual cells. Despite the different patterns obtained by using Raman and infrared spectral data as input for clustering algorithms, our findings showed high data reproducibility in both approaches as the biological replicates from each bacterial strain clustered together. Overall, we show that Raman and infrared spectroscopy offer both advantages and disadvantages and, therefore, having both techniques combined in one single technology is a powerful tool with promising applications in clinical microbiology.

O-PTIR was used for simultaneous collection of infrared and Raman spectra from clinical pathogens associated with bloodstream infections.

Genetic and phylogenetic analysis of dissimilatory iodate-reducing bacteria identifies potential niches across the world's oceans

Iodine is oxidized and reduced as part of a biogeochemical cycle that is especially pronounced in the oceans, where the element naturally concentrates. The use of oxidized iodine in the form of iodate (IO3-) as an electron acceptor by microorganisms is poorly understood. Here, we outline genetic, physiological, and ecological models for dissimilatory IO3- reduction to iodide (I-) by a novel estuarine bacterium, Denitromonas sp. IR-12. Our results show that dissimilatory iodate reduction (DIR) by strain IR-12 is molybdenum-dependent and requires an IO3- reductase (idrA) and likely other genes in a mobile cluster with a conserved association across known and predicted DIR microorganisms (DIRM). Based on genetic and physiological data, we propose a model where three molecules of IO3- are likely reduced to three molecules of hypoiodous acid (HIO), which rapidly disproportionate into one molecule of IO3- and two molecules of iodide (I-), in a respiratory pathway that provides an energy yield equivalent to that of nitrate or perchlorate respiration. Consistent with the ecological niche expected of such a metabolism, idrA is enriched in the metagenome sequence databases of marine sites with a specific biogeochemical signature (high concentrations of nitrate and phosphate) and diminished oxygen. Taken together, these data suggest that DIRM help explain the disequilibrium of the IO3-:I- concentration ratio above oxygen-minimum zones and support a widespread iodine redox cycle mediated by microbiology.

Phosphorus Concentration in Water Affects the Biofilm Community and the Produced Amount of Extracellular Polymeric Substances in Reverse Osmosis Membrane Systems

Biofouling is a problem that hinders sustainable membrane-based desalination and the stratification of bacterial populations over the biofilm's height is suggested to compromise the efficiency of cleaning strategies. Some studies reported a base biofilm layer attached to the membrane that is harder to remove. Previous research suggested limiting the concentration of phosphorus in the feed water as a biofouling control strategy. However, the existence of bacterial communities growing under phosphorus-limiting conditions and communities remaining after cleaning is unknown. This study analyzes the bacterial communities developed in biofilms grown in membrane fouling simulators (MFSs) supplied with water with three dosed phosphorus conditions at a constant biodegradable carbon concentration. After biofilm development, biofilm was removed using forward flushing (an easy-to-implement and environmentally friendly method) by increasing the crossflow velocity for one hour. We demonstrate that small changes in phosphorus concentration in the feed water led to (i) different microbial compositions and (ii) different bacterial-cells-to-EPS ratios, while (iii) similar bacterial biofilm populations remained after forward flushing, suggesting a homogenous bacterial community composition along the biofilm height. This study represents an exciting advance towards greener desalination by applying non-expensive physical cleaning methods while manipulating feed water nutrient conditions to prolong membrane system performance and enhance membrane cleanability.

Robust surface-to-mass coupling and turgor-dependent cell width determine bacterial dry-mass density

Intracellular biomass density is an important variable for cellular physiology. It defines the crowded state of the cytoplasm and thus influences macromolecular interactions and transport. To control density during growth, bacteria must expand their cell volumes in synchrony with biomass. The regulation of volume growth and biomass density remain fundamentally not understood—in bacteria or any other organism. Using advanced microscopy, we demonstrate that cells control dry-mass density indirectly through two independent processes. First, cells expand surface area, rather than volume, in proportion with biomass growth. Second, cell width is controlled independently, with an important influence of turgor pressure. Our findings overturn a long-standing paradigm of mass-density constancy in bacteria and reveal fundamental determinants of dry-mass density and shape.

During growth, cells must expand their cell volumes in coordination with biomass to control the level of cytoplasmic macromolecular crowding. Dry-mass density, the average ratio of dry mass to volume, is roughly constant between different nutrient conditions in bacteria, but it remains unknown whether cells maintain dry-mass density constant at the single-cell level and during nonsteady conditions. Furthermore, the regulation of dry-mass density is fundamentally not understood in any organism. Using quantitative phase microscopy and an advanced image-analysis pipeline, we measured absolute single-cell mass and shape of the model organisms Escherichia coli and Caulobacter crescentus with improved precision and accuracy. We found that cells control dry-mass density indirectly by expanding their surface, rather than volume, in direct proportion to biomass growth—according to an empirical surface growth law. At the same time, cell width is controlled independently. Therefore, cellular dry-mass density varies systematically with cell shape, both during the cell cycle or after nutrient shifts, while the surface-to-mass ratio remains nearly constant on the generation time scale. Transient deviations from constancy during nutrient shifts can be reconciled with turgor-pressure variations and the resulting elastic changes in surface area. Finally, we find that plastic changes of cell width after nutrient shifts are likely driven by turgor variations, demonstrating an important regulatory role of mechanical forces for width regulation. In conclusion, turgor-dependent cell width and a slowly varying surface-to-mass coupling constant are the independent variables that determine dry-mass density.

Intraspecific trait variation alters the outcome of competition in freshwater ciliates

Trait variation among heterospecific and conspecific organisms may substantially affect community and food web dynamics. While the relevance of competition and feeding traits have been widely studied for different consumer species, studies on intraspecific differences are more scarce, partly owing to difficulties in distinguishing different clones of the same species. Here, we investigate how intraspecific trait variation affects the competition between the freshwater ciliates Euplotes octocarinatus and Coleps hirtus in a nitrogen-limited chemostat system. The ciliates competed for the microalgae Cryptomonas sp. (Cry) and Navicula pelliculosa (Nav), and the bacteria present in the cultures over a period of 33 days. We used monoclonal Euplotes and three different Coleps clones (Col 1, Col 2, and Col 3) in the experiment that could be distinguished by a newly developed rDNA-based molecular assay based on the internal transcribed spacer (ITS) regions. While Euplotes feeds on Cry and on bacteria, the Coleps clones cannot survive on bacteria alone but feed on both Cry and Nav with clone-specific rates. Experimental treatments comprised two-species mixtures of Euplotes and one or all of the three different Coleps clones, respectively. We found intraspecific variation in the traits "selectivity" and "maximum ingestion rate" for the different algae to significantly affect the competitive outcome between the two ciliate species. As Nav quickly escaped top-down control and likely reached a state of low food quality, ciliate competition was strongly determined by the preference of different Coleps clones for Cry as opposed to feeding on Nav. In addition, the ability of Euplotes to use bacteria as an alternative food source strengthened its persistence once Cry was depleted. Hence, trait variation at both trophic levels codetermined the population dynamics and the outcome of species competition.

Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities

The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood.

Microbial communities play a key role in biogeochemical cycles, bioremediation, and human health. In crowded microbial systems such as biofilms and cellular aggregates, the close proximity between individual cells reduces the free space for the nutrients diffusion. To model the heterogeneous nature of these microbial systems, we developed CROMICS, a framework that integrates the information about the metabolic capabilities of each individual cell as well as the size and location of cells and macromolecules in the medium. The interactions among the individuals arise naturally through competition for or the exchange of metabolites. We show how the presence of mutants and a reduced diffusion in crowded environments can perturb the local availability of nutrients and therefore modify the dynamics of a microbial community. The discovered mechanisms underlying the microbial interactions in crowded systems together with the developed framework represent a valuable starting point for future studies of the interplay of human microbiome and host metabolism, the pathogen invasion, and the evaluation of antibiotic effectiveness.

Nanoceutical Fabric Prevents COVID-19 Spread through Expelled Respiratory Droplets: A Combined Computational, Spectroscopic, and Antimicrobial Study

Centers for Disease Control and Prevention (CDC) warns the use of one-way valves or vents in face masks for potential threat of spreading COVID-19 through expelled respiratory droplets. Here, we have developed a nanoceutical cotton fabric duly sensitized with non-toxic zinc oxide nanomaterial for potential use as a membrane filter in the one-way valve for the ease of breathing without the threat of COVID-19 spreading. A detailed computational study revealed that zinc oxide nanoflowers (ZnO NFs) with almost two-dimensional petals trap SARS-CoV-2 spike proteins, responsible to attach to ACE-2 receptors in human lung epithelial cells. The study also confirmed significant denaturation of the spike proteins on the ZnO surface, revealing removal of the virus upon efficient trapping. Following the computational study, we have synthesized ZnO NF on a cotton matrix using a hydrothermal-assisted strategy. Electron-microscopic, steady-state, and picosecond-resolved spectroscopic studies confirm attachment of ZnO NF to the cotton (i.e., cellulose) matrix at the atomic level to develop the nanoceutical fabric. A detailed antimicrobial assay using Pseudomonas aeruginosa bacteria (model SARS-CoV-2 mimic) reveals excellent antimicrobial efficiency of the developed nanoceutical fabric. To our understanding, the nanoceutical fabric used in the one-way valve of a face mask would be the choice to assure breathing comfort along with source control of COVID-19 infection. The developed nanosensitized cloth can also be used as an antibacterial/anti CoV-2 washable dress material in general.

Nanoceutical Fabric Prevents COVID-19 Spread through Expelled Respiratory Droplets: A Combined Computational, Spectroscopic, and Antimicrobial Study

Centers for Disease Control and Prevention (CDC) warns the use of one-way valves or vents in face masks for potential threat of spreading COVID-19 through expelled respiratory droplets. Here, we have developed a nanoceutical cotton fabric duly sensitized with non-toxic zinc oxide nanomaterial for potential use as a membrane filter in the one-way valve for the ease of breathing without the threat of COVID-19 spreading. A detailed computational study revealed that zinc oxide nanoflowers (ZnO NFs) with almost two-dimensional petals trap SARS-CoV-2 spike proteins, responsible to attach to ACE-2 receptors in human lung epithelial cells. The study also confirmed significant denaturation of the spike proteins on the ZnO surface, revealing removal of the virus upon efficient trapping. Following the computational study, we have synthesized ZnO NF on a cotton matrix using a hydrothermal-assisted strategy. Electron-microscopic, steady-state, and picosecond-resolved spectroscopic studies confirm attachment of ZnO NF to the cotton (i.e., cellulose) matrix at the atomic level to develop the nanoceutical fabric. A detailed antimicrobial assay using Pseudomonas aeruginosa bacteria (model SARS-CoV-2 mimic) reveals excellent antimicrobial efficiency of the developed nanoceutical fabric. To our understanding, the nanoceutical fabric used in the one-way valve of a face mask would be the choice to assure breathing comfort along with source control of COVID-19 infection. The developed nanosensitized cloth can also be used as an antibacterial/anti CoV-2 washable dress material in general.

Isolation, characterization, anti-MRSA evaluation, and in-silico multi-target anti-microbial validations of actinomycin X2 and actinomycin D produced by novel Streptomyces smyrnaeus UKAQ_23

Streptomyces smyrnaeus UKAQ_23, isolated from the mangrove-sediment, collected from Jubail,Saudi Arabia, exhibited substantial antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA), including non-MRSA Gram-positive test bacteria. The novel isolate, under laboratory-scale conditions, produced the highest yield (561.3 ± 0.3 mg/kg fermented agar) of antimicrobial compounds in modified ISP-4 agar at pH 6.5, temperature 35 °C, inoculum 5% v/w, agar 1.5% w/v, and an incubation period of 7 days. The two major compounds, K1 and K2, were isolated from fermented medium and identified as Actinomycin X2 and Actinomycin D, respectively, based on their structural analysis. The antimicrobial screening showed that Actinomycin X2 had the highest antimicrobial activity compared to Actinomycin D, and the actinomycins-mixture (X2:D, 1:1, w/w) against MRSA and non-MRSA Gram-positive test bacteria, at 5 µg/disc concentrations. The MIC of Actinomycin X2 ranged from 1.56-12.5 µg/ml for non-MRSA and 3.125-12.5 µg/ml for MRSA test bacteria. An in-silico molecular docking demonstrated isoleucyl tRNA synthetase as the most-favored antimicrobial protein target for both actinomycins, X2 and D, while the penicillin-binding protein-1a, was the least-favorable target-protein. In conclusion, Streptomyces smyrnaeus UKAQ_23 emerged as a promising source of Actinomycin X2 with the potential to be scaled up for industrial production, which could benefit the pharmaceutical industry.

First Insights into the Microbiology of Three Antarctic Briny Systems of the Northern Victoria Land

Different polar environments (lakes and glaciers), also in Antarctica, encapsulate brine pools characterized by a unique combination of extreme conditions, mainly in terms of high salinity and low temperature. Since 2014, we have been focusing our attention on the microbiology of brine pockets from three lakes in the Northern Victoria Land (NVL), lying in the Tarn Flat (TF) and Boulder Clay (BC) areas. The microbial communities have been analyzed for community structure by next generation sequencing, extracellular enzyme activities, metabolic potentials, and microbial abundances. In this study, we aim at reconsidering all available data to analyze the influence exerted by environmental parameters on the community composition and activities. Additionally, the prediction of metabolic functions was attempted by the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2) tool, highlighting that prokaryotic communities were presumably involved in methane metabolism, aromatic compound biodegradation, and organic compound (proteins, polysaccharides, and phosphates) decomposition. The analyzed cryoenvironments were different in terms of prokaryotic diversity, abundance, and retrieved metabolic pathways. By the analysis of DNA sequences, common operational taxonomic units ranged from 2.2% to 22.0%. The bacterial community was dominated by Bacteroidetes. In both BC and TF brines, sequences of the most thermally tolerant and methanogenic Archaea were detected, some of them related to hyperthermophiles.

The influence of the crowding assumptions in biofilm simulations

Microorganisms are frequently organized into crowded structures that affect the nutrients diffusion. This reduction in metabolite diffusion could modify the microbial dynamics, meaning that computational methods for studying microbial systems need accurate ways to model the crowding conditions. We previously developed a computational framework, termed CROMICS, that incorporates the effect of the (time-dependent) crowding conditions on the spatio-temporal modeling of microbial communities, and we used it to demonstrate the crowding influence on the community dynamics. To further identify scenarios where crowding should be considered in microbial modeling, we herein applied and extended CROMICS to simulate several environmental conditions that could potentially boost or dampen the crowding influence in biofilms. We explore whether the nutrient supply (rich- or low-nutrient media), the cell-packing configuration (square or hexagonal spherical cell arrangement), or the cell growing conditions (planktonic state or biofilm) modify the crowding influence on the growth of Escherichia coli. Our results indicate that the growth rate, the abundance and appearance time of different cell phenotypes as well as the amount of by-products secreted to the medium are sensitive to some extent to the local crowding conditions in all scenarios tested, except in rich-nutrient media. Crowding conditions enhance the formation of nutrient gradient in biofilms, but its effect is only appreciated when cell metabolism is controlled by the nutrient limitation. Thus, as soon as biomass (and/or any other extracellular macromolecule) accumulates in a region, and cells occupy more than 14% of the volume fraction, the crowding effect must not be underestimated, as the microbial dynamics start to deviate from the ideal/expected behaviour that assumes volumeless cells or when a homogeneous (reduced) diffusion is applied in the simulation. The modeling and simulation of the interplay between the species diversity (cell shape and metabolism) and the environmental conditions (nutrient quality, crowding conditions) can help to design effective strategies for the optimization and control of microbial systems.

Assessment of Isoprene as a Possible Biosignature Gas in Exoplanets with Anoxic Atmospheres

The search for possible biosignature gases in habitable exoplanet atmospheres is accelerating, although actual observations are likely years away. This work adds isoprene, C₅H₈, to the roster of biosignature gases. We found that isoprene geochemical formation is highly thermodynamically disfavored and has no known abiotic false positives. The isoprene production rate on Earth rivals that of methane (CH₄; ∼500 Tg/year). Unlike methane, on Earth isoprene is rapidly destroyed by oxygen-containing radicals. Although isoprene is predominantly produced by deciduous trees, isoprene production is ubiquitous to a diverse array of evolutionary distant organisms, from bacteria to plants and animals-few, if any, volatile secondary metabolites have a larger evolutionary reach. Although non-photochemical sinks of isoprene may exist, such as degradation of isoprene by life or other high deposition rates, destruction of isoprene in an anoxic atmosphere is mainly driven by photochemistry. Motivated by the concept that isoprene might accumulate in anoxic environments, we model the photochemistry and spectroscopic detection of isoprene in habitable temperature, rocky exoplanet anoxic atmospheres with a variety of atmosphere compositions under different host star ultraviolet fluxes. Limited by an assumed 10 ppm instrument noise floor, habitable atmosphere characterization when using James Webb Space Telescope (JWST) is only achievable with a transit signal similar or larger than that for a super-Earth-sized exoplanet transiting an M dwarf star with an H₂-dominated atmosphere. Unfortunately, isoprene cannot accumulate to detectable abundance without entering a run-away phase, which occurs at a very high production rate, ∼100 times the Earth's production rate. In this run-away scenario, isoprene will accumulate to >100 ppm, and its spectral features are detectable with ∼20 JWST transits. One caveat is that some isoprene spectral features are hard to distinguish from those of methane and also from other hydrocarbons containing the isoprene substructure. Despite these challenges, isoprene is worth adding to the menu of potential biosignature gases.

Evolutionarily Stable Coevolution Between a Plastic Lytic Virus and Its Microbial Host

Hosts influence and are influenced by viral replication. Cell size, for example, is a fundamental trait for microbial hosts that can not only alter the probability of viral adsorption, but also constrain the host physiological processes that the virus relies on to replicate. This intrinsic connection can affect the fitness of both host and virus, and therefore their mutual evolution. Here, we study the coevolution of bacterial hosts and their viruses by considering the dependence of viral performance on the host physiological state (viral plasticity). To this end, we modified a standard host-lytic phage model to include viral plasticity, and compared the coevolutionary strategies emerging under different scenarios, including cases in which only the virus or the host evolve. For all cases, we also obtained the evolutionary prediction of the traditional version of the model, which assumes a non-plastic virus. Our results reveal that the presence of the virus leads to an increase in host size and growth rate in the long term, which benefits both interacting populations. Our results also show that viral plasticity and evolution influence the classic host quality-quantity trade-off. Poor nutrient environments lead to abundant low-quality hosts, which tends to increase viral infection time. Conversely, richer nutrient environments lead to fewer but high-quality hosts, which decrease viral infection time. Our results can contribute to advancing our understanding of the microbial response to changing environments. For instance, both cell size and viral-induced mortality are essential factors that determine the structure and dynamics of the marine microbial community, and therefore our study can improve predictions of how marine ecosystems respond to environmental change. Our study can also help devise more reliable strategies to use phage to, for example, fight bacterial infections.

Measuring and modeling energy and power consumption in living microbial cells with a synthetic ATP reporter

Background

Adenosine triphosphate (ATP) is the main energy carrier in living organisms, critical for metabolism and essential physiological processes. In humans, abnormal regulation of energy levels (ATP concentration) and power consumption (ATP consumption flux) in cells is associated with numerous diseases from cancer, to viral infection and immune dysfunction, while in microbes it influences their responses to drugs and other stresses. The measurement and modeling of ATP dynamics in cells is therefore a critical component in understanding fundamental physiology and its role in pathology. Despite the importance of ATP, our current understanding of energy dynamics and homeostasis in living cells has been limited by the lack of easy-to-use ATP sensors and the lack of models that enable accurate estimates of energy and power consumption related to these ATP dynamics. Here we describe a dynamic model and an ATP reporter that tracks ATP in E. coli over different growth phases.

Results

The reporter is made by fusing an ATP-sensing rrnB P1 promoter with a fast-folding and fast-degrading GFP. Good correlations between reporter GFP and cellular ATP were obtained in E. coli growing in both minimal and rich media and in various strains. The ATP reporter can reliably monitor bacterial ATP dynamics in response to nutrient availability. Fitting the dynamics of experimental data corresponding to cell growth, glucose, acetate, dissolved oxygen, and ATP yielded a mathematical and circuit model. This model can accurately predict cellular energy and power consumption under various conditions. We found that cellular power consumption varies significantly from approximately 0.8 and 0.2 million ATP/s for a tested strain during lag and stationary phases to 6.4 million ATP/s during exponential phase, indicating ~ 8–30-fold changes of metabolic rates among different growth phases. Bacteria turn over their cellular ATP pool a few times per second during the exponential phase and slow this rate by ~ 2–5-fold in lag and stationary phases.

Conclusion

Our rrnB P1-GFP reporter and kinetic circuit model provide a fast and simple way to monitor and predict energy and power consumption dynamics in bacterial cells, which can impact fundamental scientific studies and applied medical treatments in the future.

Assessing Biodegradability of Chemical Compounds from Microbial Community Growth Using Flow Cytometry

Compound biodegradability tests with natural microbial communities form an important keystone in the ecological assessment of chemicals. However, biodegradability tests are frequently limited by a singular focus either on the chemical and potential transformation products or on the individual microbial species degrading the compound. Here, we investigated a methodology to simultaneously analyze community compositional changes and biomass growth on dosed test compound from flow cytometry (FCM) data coupled to machine-learned cell type recognition. We quantified the growth of freshwater microbial communities on a range of carbon dosages of three readily biodegradable reference compounds, phenol, 1-octanol, and benzoate, in comparison to three fragrances, methyl jasmonate, myrcene, and musk xylene (as a nonbiodegradable control). Compound mass balances with between 0.1 to 10 mg C · liter-1 phenol or 1-octanol, inferred from cell numbers, parent compound analysis, and CO2 evolution, as well as use of 14C-labeled compounds, showed between 6 and 25% mg C · mg C-1 substrate incorporation into biomass within 2 to 4 days and 25 to 45% released as CO2 In contrast, similar dosage of methyl jasmonate and myrcene supported slower (4 to 10 days) and less (2.6 to 6.6% mg C · mg C-1 with 4.9 to 22% CO2) community growth. Community compositions inferred from machine-learned cell type recognition and 16S rRNA amplicon sequencing showed substrate- and concentration-dependent changes, with visible enrichment of microbial subgroups already at 0.1 mg C · liter-1 phenol and 1-octanol. In general, community compositions were similar at the start and after the stationary phase of the microbial growth, except at the highest used substrate concentrations of 100 to 1,000 mg C · liter-1 Flow cytometry cell counting coupled to deconvolution of communities into subgroups is thus suitable to infer biodegradability of organic chemicals, permitting biomass balances and near-real-time assessment of relevant subgroup changes.IMPORTANCE The manifold effects of potentially toxic compounds on microbial communities are often difficult to discern. Some compounds may be transformed or completely degraded by few or multiple strains in the community, whereas others may present inhibitory effects. In this study, we benchmark a new method based on machine-learned microbial cell recognition to rapidly follow dynamic changes in aquatic communities. We further determine productive biodegradation upon dosing of a number of well-known readily biodegradable tester compounds at a variety of concentrations. Microbial community growth was quantified using flow cytometry, and the multiple cell parameters measured were used in parallel to deconvolute the community on the basis of similarity to previously standardized cell types. Biodegradation was further confirmed by chemical analysis, showing how distinct changes in specific populations correlate to degradation. The method holds great promise for near-real-time community composition changes and deduction of compound biodegradation in natural microbial communities.

Novel allosteric inhibition of phosphoribulokinase identified by ensemble kinetic modeling of Synechocystis sp. PCC 6803 metabolism

The present study attempted a computer simulation of the metabolism of a model cyanobacteria, Synechocystis sp. PCC 6803 (PCC 6803) to predict allosteric inhibitions that are likely to occur in photoautotrophic and mixotrophic conditions as well as in a metabolically engineered strain. PCC 6803 is a promising host for direct biochemical production from CO₂; however, further investigation of allosteric regulation is required for rational metabolic engineering to produce target compounds. Herein, ensemble modeling of microbial metabolism was applied to build accurate predictive models by synthesizing the results of multiple models with different parameter sets into a single score to identify plausible allosteric inhibitions. The data driven-computer simulation using metabolic flux, enzyme abundance, and metabolite concentration data successfully identified candidates for allosteric inhibition. The enzyme assay experiment using the recombinant protein confirmed isocitrate was a non-competitive inhibitor of phosphoribulokinase as a novel allosteric regulation of cyanobacteria metabolism.

Modeling a co-culture of Clostridium autoethanogenum and Clostridium kluyveri to increase syngas conversion to medium-chain fatty-acids

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We model a co-culture of C. autoethanogenum and C. kluyveri for syngas fermentation.

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Biomass species ratio affects ethanol and acetate profiles in the co-culture.

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The model predicts that addition of succinate increases caproate production.

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Genetic interventions  in C. autoethanogenum could increase caproate production.

Microbial fermentation of synthesis gas (syngas) is becoming more attractive for sustainable production of commodity chemicals. To date, syngas fermentation focuses mainly on the use of Clostridium species for the production of small organic molecules such as ethanol and acetate. The co-cultivation of syngas-fermenting microorganisms with chain-elongating bacteria can expand the range of possible products, allowing, for instance, the production of medium-chain fatty acids (MCFA) and alcohols from syngas. To explore these possibilities, we report herein a genome-scale, constraint-based metabolic model to describe growth of a co-culture of Clostridium autoethanogenum and Clostridium kluyveri on syngas for the production of valuable compounds. Community flux balance analysis was used to gain insight into the metabolism of the two strains and their interactions, and to reveal potential strategies enabling production of butyrate and hexanoate.

The model suggests that one strategy to optimize the production of medium-chain fatty-acids from syngas would be the addition of succinate. According to the prediction, addition of succinate would increase the pool of crotonyl-CoA and the ethanol/acetate uptake ratio in C. kluyveri, resulting in a flux of up to 60% of electrons into hexanoate. Another potential way to further optimize butyrate and hexanoate production would be an increase of C. autoethanogenum ethanol production. Blocking either acetaldehyde dehydrogenase or formate dehydrogenase (ferredoxin) activity or formate transport, in the C. autoethanogenum metabolic model could potentially lead to an up to 150% increase in ethanol production.

Microbial carrying capacity and carbon biomass of plastic marine debris

Trillions of plastic debris fragments are floating at sea, presenting a substantial surface area for microbial colonization. Numerous cultivation-independent surveys have characterized plastic-associated microbial biofilms, however, quantitative studies addressing microbial carbon biomass are lacking. Our confocal laser scanning microscopy data show that early biofilm development on polyethylene, polypropylene, polystyrene, and glass substrates displayed variable cell size, abundance, and carbon biomass, whereas these parameters stabilized in mature biofilms. Unexpectedly, plastic substrates presented lower volume proportions of photosynthetic cells after 8 weeks, compared to glass. Early biofilms displayed the highest proportions of diatoms, which could influence the vertical transport of plastic debris. In total, conservative estimates suggest 2.1 × 10²¹ to 3.4 × 10²¹ cells, corresponding to about 1% of the microbial cells in the ocean surface microlayer (1.5 × 10³ to 1.1 × 10⁴ tons of carbon biomass), inhabit plastic debris globally. As an unnatural addition to sea surface waters, the large quantity of cells and biomass carried by plastic debris has the potential to impact biodiversity, autochthonous ecological functions, and biogeochemical cycles within the ocean.

Mass Spectrometry of Heavy Analytes and Large Biological Aggregates by Monitoring Changes in the Quality Factor of Nanomechanical Resonators in Air

Nanomechanical resonators are routinely used for identification of various analytes such as biological and chemical molecules, viruses, or bacteria cells from the frequency response. This identification based on the multimode frequency shift measurement is limited to the analyte of mass that is much lighter than the resonator mass. Hence, the analyte can be modeled as a point particle and, as such, its stiffness and nontrivial binding effects such as surface stress can be neglected. For heavy analytes (>MDa), this identification, however, leads to incorrectly estimated masses. Using a well-known frequency response of the nanomechanical resonator in air, we show that the heavy analyte can be identified without a need for highly challenging analysis of the analyte position, stiffness, and/or binding effects just by monitoring changes in the quality factor (Q-factor) of a single harmonic frequency. A theory with a detailed procedure of mass extraction from the Q-factor is developed. In air, the Q-factor depends on the analyte mass and known air damping, while the impact of the intrinsic dissipation is negligibly small. We find that the highest mass sensitivity (for considered resonator dimensions ∼zg) can be achieved for the rarely measured lateral mode, whereas the commonly detected flexural mode yields the lowest sensitivity. Validity of the proposed procedure is confirmed by extracting the mass of heavy analytes (>GDa) made of protein and Escherichia coli bacteria cells, and the ragweed pollen nanoparticle adsorbed on the surface of the nanomechanical resonator(s) in air, of which the required changes in the Q-factor were previously experimentally measured. Our results open a doorway for rapid detection of viruses and bacteria cells using standard nanomechanical mass sensors.

Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data

The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learning algorithm of standard cell type recognition (CellCognize). As a proof-of-concept, we trained neural networks with 32 microbial cell and bead standards. The resulting classifiers were extensively validated in silico on known microbiota, showing on average 80% prediction accuracy. Furthermore, the classifiers could detect shifts in microbial communities of unknown composition upon chemical amendment, comparable to results from 16S-rRNA-amplicon analysis. CellCognize was also able to quantify population growth and estimate total community biomass productivity, providing estimates similar to those from ¹⁴C-substrate incorporation. CellCognize complements current sequencing-based methods by enabling rapid routine cell diversity analysis. The pipeline is suitable to optimize cell recognition for recurring microbiota types, such as in human health or engineered systems.

Duygan et al. develop a supervised machine learning algorithm, CellCognize, to quantify cell type diversity from multidimensional flow cytometry data. Their model achieves 80% prediction accuracy, detects shifts in microbial communities of unknown composition and quantifies population growth and biomass productivity. Their work will be useful to study microbiota in human health or engineered systems.