Micron Scale Spatial Measurement of the O2 Gradient Surrounding a Bacterial Biofilm in Real Time

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae (Hp) is a Gram-negative, highly prevalent, and abundant commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the supragingival plaque biofilm. Little is known about how Hp interacts with its neighbors in healthy biofilms nor its mechanisms of pathogenesis as an opportunistic pathogen. To address this, we identified the essential genome and conditionally essential genes in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain (Hp 392) and oral isolate EL1 (Hp EL1), we show that the essential genomes of Hp 392 and Hp EL1 are composed of 395 (20%) and 384 (19%) genes, respectively. The core essential genome, consisting of 341 (17%) essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains. RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo habitat. This library presents a valuable tool for investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.IMPORTANCEHaemophilus parainfluenzae is a highly abundant human commensal microbe, present in most healthy individuals where it colonizes the mouth. H. parainfluenzae correlates with good oral health and may play a role in preservation of healthy host status. Also, H. parainfluenzae can cause opportunistic infections outside of the oral cavity. To date, little is known about how H. parainfluenzae colonizes the human host, despite being such a frequent and abundant part of our human microbiome. Here, we demonstrate the creation and use of a powerful tool, a TnSeq library, used to identify genes necessary for both the outright growth of this organism and also genes conditionally essential for growth in varying oxygen status which it can encounter in the human host. This tool and these data serve as a foundation for further study of this relatively unknown organism that may play a role in preserving human health.

Essential genes for Haemophilus parainfluenzae survival and biofilm growth

Haemophilus parainfluenzae ( Hp ) is a Gram-negative, pleomorphic rod, highly prevalent and abundant as a commensal in the human oral cavity, and an infrequent extraoral opportunistic pathogen. Hp occupies multiple niches in the oral cavity, including the tongue dorsum, keratinized gingiva, and the supragingival plaque biofilm. As a member of the HACEK group, Hp is also known to cause infective endocarditis. Additionally, case reports have identified Hp as the causative agent of meningitis, septic arthritis, chronic osteomyelitis, septicemia, and a variety of other infectious diseases. Little is known about how Hp interacts with its neighbors in the healthy biofilm nor about its mechanisms of pathogenesis as an extraoral opportunistic pathogen. To address these unknowns, we identified the essential genomes of two Hp strains and the conditionally essential genes for their growth in in vitro biofilms aerobically and anaerobically. Using transposon insertion sequencing (TnSeq) with a highly saturated mariner transposon library in two strains, the ATCC33392 type-strain ( Hp 392) and a commensal oral isolate EL1 ( Hp EL1), we show that the essential genome of Hp 392 and Hp EL1 is composed of 395 and 384 genes, respectively. The core essential genome, consisting of 341 essential genes conserved between both strains, was composed of genes associated with genetic information processing, carbohydrate, protein, and energy metabolism. We also identified conditionally essential genes for aerobic and anaerobic biofilm growth, which were associated with carbohydrate and energy metabolism in both strains of Hp . Additionally, RNAseq analysis determined that most genes upregulated during anaerobic growth are not essential for Hp 392 anaerobic biofilm survival. The completion of this library and analysis under these conditions gives us a foundational insight into the basic biology of H. parainfluenzae in differing oxygen conditions, similar to its in vivo oral habitat. Further, the creation of this library presents a valuable tool for further investigation into conditionally essential genes for an organism that lives in close contact with many microbial species in the human oral habitat.

Cellular arrangement impacts metabolic activity and antibiotic tolerance in Pseudomonas aeruginosa biofilms

Cells must access resources to survive, and the anatomy of multicellular structures influences this access. In diverse multicellular eukaryotes, resources are provided by internal conduits that allow substances to travel more readily through tissue than they would via diffusion. Microbes growing in multicellular structures, called biofilms, are also affected by differential access to resources and we hypothesized that this is influenced by the physical arrangement of the cells. In this study, we examined the microanatomy of biofilms formed by the pathogenic bacterium Pseudomonas aeruginosa and discovered that clonal cells form striations that are packed lengthwise across most of a mature biofilm's depth. We identified mutants, including those defective in pilus function and in O-antigen attachment, that show alterations to this lengthwise packing phenotype. Consistent with the notion that cellular arrangement affects access to resources within the biofilm, we found that while the wild type shows even distribution of tested substrates across depth, the mutants show accumulation of substrates at the biofilm boundaries. Furthermore, we found that altered cellular arrangement within biofilms affects the localization of metabolic activity, the survival of resident cells, and the susceptibility of subpopulations to antibiotic treatment. Our observations provide insight into cellular features that determine biofilm microanatomy, with consequences for physiological differentiation and drug sensitivity.

A Brief Review of In Situ and Operando Electrochemical Analysis of Bacteria by Scanning Probes

Bacteria are similar to social organisms that engage in critical interactions with one another, forming spatially structured communities. Despite extensive research on the composition, structure, and communication of bacteria, the mechanisms behind their interactions and biofilm formation are not yet fully understood. To address this issue, scanning probe techniques such as atomic force microscopy (AFM), scanning electrochemical microscopy (SECM), scanning electrochemical cell microscopy (SECCM), and scanning ion-conductance microscopy (SICM) have been utilized to analyze bacteria. This review article focuses on summarizing the use of electrochemical scanning probes for investigating bacteria, including analysis of electroactive metabolites, enzymes, oxygen consumption, ion concentrations, pH values, biofilms, and quorum sensing molecules to provide a better understanding of bacterial interactions and communication. SECM has been combined with other techniques, such as AFM, inverted optical microscopy, SICM, and fluorescence microscopy. This allows a comprehensive study of the surfaces of bacteria while also providing more information on their metabolic activity. In general, the use of scanning probes for the detection of bacteria has shown great promise and has the potential to provide a powerful tool for the study of bacterial physiology and the detection of bacterial infections.

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure.

Ultraviolet control of bacterial biofilms in microfluidic chips

Polydimethylsiloxane (PDMS) microfluidic systems have been instrumental in better understanding couplings between physical mechanisms and bacterial biofilm processes, such as hydrodynamic effects. However, precise control of the growth conditions, for example, the initial distribution of cells on the substrate or the boundary conditions in a flow system, has remained challenging. Furthermore, undesired bacterial colonization in crucial parts of the systems, in particular, in mixing zones or tubing, is an important factor that strongly limits the duration of the experiments and, therefore, impedes our ability to study the biophysics of biofilm evolving over long periods of time, as found in the environment, in engineering, or in medicine. Here, we develop a new approach that uses ultraviolet-C (UV-C) light-emitting diodes (LEDs) to confine bacterial development to specific zones of interest in the flow channels. The LEDs are integrated into a 3D printed light guide that is positioned upon the chip and used to irradiate germicidal UV-C directly through the PDMS. We first demonstrate that this system is successful in controlling undesired growth of Pseudomonas aeruginosa biofilm in inlet and outlet mixing zones during 48 h. We further illustrate how this can be used to define the initial distribution of bacteria to perturb already formed biofilms during an experiment and to control colonization for seven days-and possibly longer periods of time-therefore opening the way toward long-term biofilm experiments in microfluidic devices. Our approach is easily generalizable to existing devices at low cost and may, thus, become a standard in biofilm experiments in PDMS microfluidics.

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O2 and H2O2

In microbiology, extracellular oxygen (O₂) and reactive oxygen species (ROS) are spatiotemporally heterogenous, ubiquitously, at macroscopic level. Such spatiotemporal heterogeneities are critical to microorganisms, yet a well-defined method of studying such heterogenous microenvironments is lacking. This work develops a machine learning–based inverse design strategy that builds an electrochemical platform for achieving spatiotemporal control of O₂ and ROS microenvironments relevant to microbiology. The inverse design strategy not only demonstrates the power of machine learning to design concentration profiles in electrochemistry but also accelerates the development of custom microenvironments for specific microbial systems and allows researchers to better study how microenvironments affect microorganisms in myriads of environmental, biomedical, and sustainability-related applications.

A fundamental understanding of extracellular microenvironments of O₂ and reactive oxygen species (ROS) such as H₂O₂, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O₂ and H₂O₂ at microscopic scale with high spatiotemporal precision. However, there is a paucity of high-throughput strategies of microenvironment design, and it remains challenging to achieve O₂ and H₂O₂ heterogeneities with microbiologically desirable spatiotemporal resolutions. Here, we report the inverse design, based on machine learning (ML), of electrochemically generated microscopic O₂ and H₂O₂ profiles relevant for microbiology. Microwire arrays with suitably designed electrochemical catalysts enable the independent control of O₂ and H₂O₂ profiles with spatial resolution of ∼10¹ μm and temporal resolution of ∼10° s. Neural networks aided by data augmentation inversely design the experimental conditions needed for targeted O₂ and H₂O₂ microenvironments while being two orders of magnitude faster than experimental explorations. Interfacing ML-based inverse design with electrochemically controlled concentration heterogeneity creates a viable fast-response platform toward better understanding the extracellular space with desirable spatiotemporal control.

Development of a Versatile, Low-Cost Electrochemical System to Study Biofilm Redox Activity at the Micron Scale

Spatially resolving chemical landscapes surrounding microbial communities can provide insight into chemical interactions that dictate cellular physiology. Electrochemical techniques provide an attractive option for studying these interactions due to their robustness and high sensitivity. Unfortunately, commercial electrochemical platforms that are capable of measuring chemical activity on the micron scale are often expensive and do not easily perform multiple scanning techniques. Here, we report development of an inexpensive electrochemical system that features a combined micromanipulator and potentiostat component capable of scanning surfaces while measuring molecular concentrations or redox profiles. We validate this experimental platform for biological use with a two-species biofilm model composed of the oral bacterial pathogen Aggregatibacter actinomycetemcomitans and the oral commensal Streptococcus gordonii. We measure consumption of H₂O₂ by A. actinomycetemcomitans biofilms temporally and spatially, providing new insights into how A. actinomycetemcomitans responds to this S. gordonii-produced metabolite. We advance our platform to spatially measure redox activity above biofilms. Our analysis supports that redox activity surrounding biofilms is species specific, and the region immediately above an S. gordonii biofilm is highly oxidized compared to that above an A. actinomycetemcomitans biofilm. This work provides description and validation of a versatile, quantitative framework for studying bacterial redox-mediated physiology in an integrated and easily adaptable experimental platform.

IMPORTANCE Scanning electrochemical probe microscopy methods can provide information of the chemical environment along a spatial surface with micron-scale resolution. These methods often require expensive instruments that perform optimized and highly sensitive niche techniques. Here, we describe a novel system that combines a micromanipulator that scans micron-sized electrodes across the surface of bacterial biofilms and a potentiostat, which performs various electrochemical techniques. This platform allows for spatial measurement of chemical gradients above live bacteria in real time, and as proof of concept, we utilize this setup to map H₂O₂ detoxification above an oral pathogen biofilm. We increased the versatility of this platform further by mapping redox potentials of biofilms in real time on the micron scale. Together, this system provides a technical framework for studying chemical interactions among microbes.

A metagenomic study of the bacteria in snow algae microbiomes

The bacterial communities found in snow algae blooms have been described in terms of their 16S rRNA gene community profiles, but little information exists on their metabolic potential. Previously, we reported that several bacterial taxa are common across snow algae blooms in the southwestern mountains of the Coast Range in British Columbia, Canada. Here, we further this work by reporting a partial bacterial metagenome from the same snow algal microbiomes. Using shotgun metagenomic data, we constructed metagenomically assembled bacterial genomes (MAGs). Of the total 54 binned MAGs, 28 were bacterial and estimated to be at least 50% complete based on single copy core genes. The 28 MAGs fell into five Classes: Actinomycetia, Alphaproteobacteria, Bacteroidia, Betaproteobacteria and Gammaproteobacteria. All MAGs were assigned to a class, 27 to an order, 25 to family, 18 to genus, and none to species. MAGs showed the potential to support algal growth by synthesizing B-vitamins and growth hormones. There was also widespread adaptation to the low oxygen environment of biofilms, including synthesis of high-affinity terminal oxidases and anaerobic pathways for cobalamin synthesis. Also notable, was the absence of N2 fixation, and the presence of incomplete denitrification pathways suggestive of NO signalling within the microbiome.

The biogeography of infection revisited

Many microbial communities, including those involved in chronic human infections, are patterned at the micron scale. In this Review, we summarize recent work that has defined the spatial arrangement of microorganisms in infection and begun to demonstrate how changes in spatial patterning correlate with disease. Advances in microscopy have refined our understanding of microbial micron-scale biogeography in samples from humans. These findings then serve as a benchmark for studying the role of spatial patterning in preclinical models, which provide experimental versatility to investigate the interplay between biogeography and pathogenesis. Experimentation using preclinical models has begun to show how spatial patterning influences the interactions between cells, their ability to coexist, their virulence and their recalcitrance to treatment. Future work to study the role of biogeography in infection and the functional biogeography of microorganisms will further refine our understanding of the interplay of spatial patterning, pathogen virulence and disease outcomes.

Gut biofilms: Bacteroides as model symbionts to study biofilm formation by intestinal anaerobes

Bacterial biofilms are communities of adhering bacteria that express distinct properties compared to their free-living counterparts, including increased antibiotic tolerance and original metabolic capabilities. Despite the potential impact of the biofilm lifestyle on the stability and function of the dense community of micro-organisms constituting the mammalian gut microbiota, the overwhelming majority of studies performed on biofilm formation by gut bacteria focused either on minor and often aerobic members of the community or on pathogenic bacteria. In this review, we discuss the reported evidence for biofilm-like structures formed by gut bacteria, the importance of considering the anaerobic nature of gut biofilms and we present the most recent advances on biofilm formation by Bacteroides, one of the most abundant genera of the human gut microbiota. Bacteroides species can be found attached to food particles and colonizing the mucus layer and we propose that Bacteroides symbionts are relevant models to probe the physiology of gut microbiota biofilms.

Spatial alanine metabolism determines local growth dynamics of Escherichia coli colonies

Bacteria commonly live in spatially structured biofilm assemblages, which are encased by an extracellular matrix. Metabolic activity of the cells inside biofilms causes gradients in local environmental conditions, which leads to the emergence of physiologically differentiated subpopulations. Information about the properties and spatial arrangement of such metabolic subpopulations, as well as their interaction strength and interaction length scales are lacking, even for model systems like Escherichia coli colony biofilms grown on agar-solidified media. Here, we use an unbiased approach, based on temporal and spatial transcriptome and metabolome data acquired during E. coli colony biofilm growth, to study the spatial organization of metabolism. We discovered that alanine displays a unique pattern among amino acids and that alanine metabolism is spatially and temporally heterogeneous. At the anoxic base of the colony, where carbon and nitrogen sources are abundant, cells secrete alanine via the transporter AlaE. In contrast, cells utilize alanine as a carbon and nitrogen source in the oxic nutrient-deprived region at the colony mid-height, via the enzymes DadA and DadX. This spatially structured alanine cross-feeding influences cellular viability and growth in the cross-feeding-dependent region, which shapes the overall colony morphology. More generally, our results on this precisely controllable biofilm model system demonstrate a remarkable spatiotemporal complexity of metabolism in biofilms. A better characterization of the spatiotemporal metabolic heterogeneities and dependencies is essential for understanding the physiology, architecture, and function of biofilms.

Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. In this work, we investigate the spatiotemporal dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen Enterococcus faecalis with plasmid-encoded β-lactamase, we track colony expansion dynamics and visualize spatial patterns in fluorescently labeled populations exposed to antibiotics. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells at otherwise lethal concentrations. The populations exhibit a diverse range of spatial segregation patterns that depend on drug concentration and initial conditions. Mathematical models indicate that the observed dynamics are consistent with global cooperation, despite the fact that β-lactamase remains cell-associated. Experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony, and populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of the drug. While biophysical models of drug degradation suggest that individual resistant cells offer only short-range protection to neighboring cells, we show that long-range protection may arise from synergistic effects of multiple resistant cells, providing surprisingly large protection zones even at small population fractions.