Chemotactic Bacteria Research Articles

Numerical Simulation of Organic Pollution Migration in the Heterogeneous Aquifer and the Application of Chemotactic Bacteria for Remediation: A Case Study of a Chemical Contamination Site in Zhejiang Province, China

Groundwater pollution poses a significant threat to ecosystems and public safety. Traditional remediation methods have limitations, necessitating innovative approaches. This study integrates numerical modeling and bioremediation to address groundwater contamination in an industrial site. It explores the potential of chemotactic bacteria to enhance remediation efficiency. The research establishes groundwater pollutant transport models, analyzes flow fields, and assesses the distribution of various pollutants. The results demonstrate the effectiveness of chemotactic bacteria, particularly chemotactic bacteria that can rapidly adapt as the pollutant concentration decreases, the concentration of chemotactic bacteria in the low-permeability area has increased by 112%. This study provides insights into the practical application of bioremediation and the promising role of bacterial chemotaxis in treating contaminated groundwater.

Multiplexed Microfluidic Platform for Parallel Bacterial Chemotaxis Assays.

The sensing of and response to ambient chemical gradients by microorganisms via chemotaxis regulates many microbial processes fundamental to ecosystem function, human health, and disease. Microfluidics has emerged as an indispensable tool for the study of microbial chemotaxis, enabling precise, robust, and reproducible control of spatiotemporal chemical conditions. Previous techniques include combining laminar flow patterning and stop-flow diffusion to produce quasi-steady chemical gradients to directly probe single-cell responses or loading micro-wells to entice and ensnare chemotactic bacteria in quasi-steady chemical conditions. Such microfluidic approaches exemplify a trade-off between high spatiotemporal resolution of cell behavior and high-throughput screening of concentration-specific chemotactic responses. However, both aspects are necessary to disentangle how a diverse range of chemical compounds and concentrations mediate microbial processes such as nutrient uptake, reproduction, and chemorepulsion from toxins. Here, we present a protocol for the multiplexed chemotaxis device (MCD), a parallelized microfluidic platform for efficient, high-throughput, and high-resolution chemotaxis screening of swimming microbes across a range of chemical concentrations. The first layer of the two-layer polydimethylsiloxane (PDMS) device comprises a serial dilution network designed to produce five logarithmically diluted chemostimulus concentrations plus a control from a single chemical solution input. Laminar flow in the second device layer brings a cell suspension and buffer solution into contact with the chemostimuli solutions in each of six separate chemotaxis assays, in which microbial responses are imaged simultaneously over time. The MCD is produced via standard photography and soft lithography techniques and provides robust,repeatable chemostimulus concentrations across each assay in the device. This microfluidic platform provides a chemotaxis assay that blends high-throughput screening approaches with single-cell resolution to achieve a more comprehensive understanding of chemotaxis-mediated microbial processes. Key features • Microchannel master molds are fabricated using photolithography techniques in a clean room with a mask aligner to fabricate multilevel feature heights. • The microfluidic device is fabricated from PDMS using standard soft lithography replica molding from the master molds. • The resulting microchannel requires a one-time calibration of the driving inlet pressures, after which devices from the same master molds have robust performance. • The microfluidic platform is optimized and tested for measuring chemotaxis of swimming prokaryotes.

Smart active particles learn and transcend bacterial foraging strategies

Throughout evolution, bacteria and other microorganisms have learned efficient foraging strategies that exploit characteristic properties of their unknown environment. While much research has been devoted to the exploration of statistical models describing the dynamics of foraging bacteria and other (micro-) organisms, little is known, regarding the question of how good the learned strategies actually are. This knowledge gap is largely caused by the absence of methods allowing to systematically develop alternative foraging strategies to compare with. In the present work, we use deep reinforcement learning to show that a smart run-and-tumble agent, which strives to find nutrients for its survival, learns motion patterns that are remarkably similar to the trajectories of chemotactic bacteria. Strikingly, despite this similarity, we also find interesting differences between the learned tumble rate distribution and the one that is commonly assumed for the run and tumble model. We find that these differences equip the agent with significant advantages regarding its foraging and survival capabilities. Our results uncover a generic route to use deep reinforcement learning for discovering search and collection strategies that exploit characteristic but initially unknown features of the environment. These results can be used, e.g., to program future microswimmers, nanorobots, and smart active particles for tasks like searching for cancer cells, micro-waste collection, or environmental remediation.

Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model.

Chemotactic bacteria not only navigate chemical gradients, but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior, and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.

Evaluation of Chemotaxis using Soft Agar Plate Method

The movement of cells in response to a chemical gradient is known as chemotaxis.An assay that is frequently used to analyze chemotaxis is the soft agar plate method. In this study, we used the soft agar plate method to examine the chemotactic migration of bacteria. On soft agar plates with a chemical attractant, bacteria were injected, and over time, their migration toward the attractant was seen. We discovered that the bacteria clearly responded to the attractant by migrating in that direction and producing discernible colonies. Our findings show how the soft agar plate approach may be used to examine the chemotactic behaviorof bacteria, and they also imply that it can be used to study the chemotactic behavior of other cell types. Chemotaxis is a biological mechanism in which specialized sensory receptors on the surface of bacteria detect chemical gradients. These receptors set off a series of events that alter the bacterial flagella motor and cause the bacterium to migrate in the direction of the chemical gradient. Several crucial bacterial processes, such as nutrition intake, host colonization, and biofilm formation, depend on chemotaxis.

Chemotaxis mediates nitrogen acquisition of maize under long-term nitrogen input

Chemotaxis is a process that enables motile bacteria to move along nutrient gradients, thereby exploring nutrient hotspots, and potentially playing important biogeochemical roles in agricultural ecosystems. In this study, a 36-year field experiment of nitrogen (N) input was conducted, along with the use of a synthetic community (SynCom) inoculation, to confirm the role of chemotaxis in the cycling of N. The chemotaxis genes abundances of N+ treatments were 97.2% and 95.3% higher than that of N- treatments in bulk soil and rhizosphere, respectively, indicating a significant increase in chemotaxis genes under long-term N input. Positive correlations between chemotaxis genes and N metabolism genes in N+ treatments suggested an important role of chemotaxis in N cycling. The chemotaxis genes abundance was 3.6 times higher in rhizosphere than in bulk soil, and chemotaxis genes showed the most complex correlations with N metabolism genes in rhizosphere under N input, suggesting a key role of chemotaxis in plant N uptake. To assess the potential function of chemotactic bacteria, a SynCom consisting of 10 bacterial strains isolated from in situ N-input soils and capable of chemotaxis, was applied to the maize rhizosphere. The promotion of N acquisition in maize plants through inoculation was confirmed by about 30% greater N content in the shoots of SynCom inoculated soil than in the control. Long-term N input enhanced the functions related to metabolite transport and energy metabolism in the bacterial community, particularly in the rhizosphere. Thus, plants may provide bacteria that migrate to the rhizosphere via chemotaxis with more root metabolites as nutrients. In summary, this study provides novel ecological and molecular insights into chemotaxis-mediated biogeochemical cycling in agricultural ecosystems.

Surface tension coupled non-uniformly imposed flows modulate the activity of reproducing chemotactic bacteria in porous media

This paper investigates a non-homogeneous two-dimensional model for reproducing chemotactic bacteria, immersed in a porous medium that experiences non-uniformly imposed flows. It is shown that independently of the form of the fluid velocity field, the compressible/incompressible nature of the fluid significantly shifts the Turing stability-instability transition line. In dry media, Gaussian perturbations travel faster than the hyperbolic secant ones, yet the latter exhibit better stability properties. The system becomes highly unstable under strong flows and high surface tension. Approximated solutions recovered by injecting Gaussian perturbations overgrow, in addition to triggering concentric breathing features that split the medium into high and low-density domains. Secant perturbations on the other hand scatter slowly and form patterns of non-uniformly distributed peaks for strong flows and high surface tension. These results emphasize that Gaussian perturbations strongly modulate the activity of bacteria, hence can be exploited to perform fast spreading in environments with changing properties. In this sense, Gaussian profiles are better candidates to explain quick bacterial responses to external factors. Secant-type approximated solutions slowly modulate the bacterial activity, hence are better alternatives to dive into weak bacterial progressions in heterogeneous media.

Porous marine snow differentially benefits chemotactic, motile, and nonmotile bacteria.

Particulate organic carbon settling through the marine water column is a key process that regulates the global climate by sequestering atmospheric carbon. The initial colonization of marine particles by heterotrophic bacteria represents the first step in recycling this carbon back to inorganic constituents-setting the magnitude of vertical carbon transport to the abyss. Here, we demonstrate experimentally using millifluidic devices that, although bacterial motility is essential for effective colonization of a particle leaking organic nutrients into the water column, chemotaxis specifically benefits at intermediate and higher settling velocities to navigate the particle boundary layer during the brief window of opportunity provided by a passing particle. We develop an individual-based model that simulates the encounter and attachment of bacterial cells with leaking marine particles to systematically evaluate the role of different parameters associated with bacterial run-and-tumble motility. We further use this model to explore the role of particle microstructure on the colonization efficiency of bacteria with different motility traits. We find that the porous microstructure facilitates additional colonization by chemotactic and motile bacteria, and fundamentally alters the way nonmotile cells interact with particles due to streamlines intersecting with the particle surface.

Pattern wavelengths and transport characteristics in three-dimensional bioconvection generated by chemotactic bacteria

We conducted a three-dimensional numerical simulation of bioconvection generated by oxygen-reactive chemotactic bacteria. This study investigated the bioconvection patterns, interference between plumes, and the wavelength of bioconvection patterns. In addition, we clarified the transport characteristics of cells and oxygen in the bioconvection. Multiple plumes occur in the suspension, and three-dimensional bioconvection is formed around the plumes by the cells with vortex rings arising around the plumes. Even if bioconvection at a high Rayleigh number is disturbed, the bioconvection is strongly stable with respect to disturbances, and the pattern does not change due to disturbances. Bioconvection changes depending on the physical properties of bacteria and oxygen, and in particular, the rate of oxygen consumption by bacteria significantly affects the strength of bioconvection. Bioconvection patterns with different plume arrangements and shapes are formed for different Rayleigh numbers or initial disturbances of the cell concentration. As a result, the wavelengths of the patterns also vary. As the Rayleigh number increases, interference between plumes is strengthened by the shortening of the pattern wavelength, so the velocities of both upward and downward flows increase. Many cells are located under the plumes, and a strong shear flow occurs in these regions. As the pattern wavelength decreases, the cells are affected by high shear stress. Then the convective transport of the entire suspension strengthens and the transport characteristics of cells and oxygen improve. When the chamber boundary is changed to side walls, bacteria adhere to the wall surface, and plumes are arranged regularly along the side walls.

Chemotaxis along local chemical gradients enhanced bacteria dispersion and PAH bioavailability in a heterogenous porous medium

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous, EPA-designated priority pollutants for soil and groundwater, remaining recalcitrant to bioremediation because of limited bioavailability. In this work, we used naphthalene as a model PAH and soil bacteria Pseudomonas putida G7 to investigate the potential role of chemotaxis to enhance access to PAHs in heterogenous porous media. To this aim, we conducted transport experiments and numerical simulations with chemotactic bacteria and naphthalene trapped within a non-aqueous phase liquid (NAPL) mainly in low permeable areas of a dual-permeability microfluidic device. Microscopic imaging showed higher accumulations of chemotactic bacteria, about eight times that of nonchemotactic bacteria, at the junctures between high and low permeability regions. Pore-scale simulations for fluid flow and naphthalene revealed that the junctures are stagnant areas of fluid flow, which generated strong and temporally persistent naphthalene gradients. The landscape and densities of bacterial accumulation at the junctures were strongly regulated by flow profiles and naphthalene gradients especially those transverse to flow. We conducted macroscale simulations using convective dispersion equations with an added chemotactic velocity to account for directed migration toward naphthalene. Simulated results showed good consistency with experiments and pore-scale simulation as normalized bacterial accumulation per mm of NAPL was 7.80, 7.84 and 7.71 mm−1 for experiments, pore-scale and macroscale simulations, respectively. Macroscale simulations indicated that in the absence of grain-boundary restrictions associated with the pore structure bacterial dispersion needed to be increased by 50 % to account for the interplay between chemotactic response and naphthalene gradients at the pore-scale level. Our work details the mechanism of pore-scale chemotaxis in enhancing bioavailability of PAHs and its impact on biomass retention at the system level, which provides a potential solution toward more efficient bioremediation for contaminants such as PAHs with limited bioavailability.

Data for publication Porous marine snow differentially benefits chemotactic, motile, and non-motile bacteria

Data for publication Porous marine snow differentially benefits chemotactic, motile, and non-motile bacteria

Root exudates and chemotactic strains mediate bacterial community assembly in the rhizosphere soil of Casuarina equisetifolia L.

Rhizosphere bacterial diversity and community structure are important factors involving in plant growth. However, the exact process of how plant rhizosphere bacterial community structures is assembled remains unclear. To investigate the role of bacterial chemotaxis to rhizosphere secretions in the establishment of rhizosphere microbial community in Casuarina equisetifolia, we screened bacteria strains derived from the rhizosphere of Casuarina equisetifolia L. using top three chemicals of the plant root exudates (2,4-di-tert-butylphenol, methyl stearate, and arginine) as chemoattractant. Among 72 bacterial strains, five showed strong chemotaxis to 2,4-di-tert-butylphenol, six to methyl stearate, and eleven to arginine, with the highest bacterial chemotaxis occurring at a concentration of 60 μM. This indicates that arginine is a more important chemoattractant than 2,4-di-tert-butylphenol, methyl stearate in the establishment of rhizosphere microbial community in Casuarina equisetifolia. Bacterial community assembly analysis using different chemoattractants and chemoattractants-plus-bacteria combinations were then performed by burying laboratory prepared bags of sterlized soil into C. equisetifolia forest. Bacteria diversity and enrichment analyses using 16S rDNA sequencing at 7 and 14 days after burying showed that arginine-plus-Ochrobactrum sp. and Pantoea sp. treatment exhibited the greatest similarity to the natural forest bacterial community. Our date provides new insights into how chemoattractants and chemotactic bacteria strains shape the rhizosphere microbial community of C. equisetifolia, which constitutes foundational information for future management of these communities.

Chemotactic Bacteria Facilitate the Dispersion of Nonmotile Bacteria through Micrometer-Sized Pores in Engineered Porous Media.

Recent research has demonstrated that chemotactic bacteria can disperse inside microsized pores while traveling toward favorable conditions. Microbe–microbe cotransport might enable nonmotile bacteria to be carried with motile partners to enhance their dispersion and reduce their deposition in porous systems. The aim of this study was to demonstrate the enhancement in the dispersion of nonmotile bacteria (Mycobacterium gilvum VM552, a polycyclic aromatic hydrocarbon-degrader, and Sphingobium sp. D4, a hexachlorocyclohexane-degrader, through micrometer-sized pores near the exclusion-cell-size limit, in the presence of motile Pseudomonas putida G7 cells. For this purpose, we used bioreactors equipped with two chambers that were separated with membrane filters with 3, 5, and 12 μm pore sizes and capillary polydimethylsiloxane (PDMS) microarrays (20 μm × 35 μm × 2.2 mm). The cotransport of nonmotile bacteria occurred exclusively in the presence of a chemoattractant concentration gradient, and therefore, a directed flow of motile cells. This cotransport was more intense in the presence of larger pores (12 μm) and strong chemoeffectors (γ-aminobutyric acid). The mechanism that governed cotransport at the cell scale involved mechanical pushing and hydrodynamic interactions. Chemotaxis-mediated cotransport of bacterial degraders and its implications in pore accessibility opens new avenues for the enhancement of bacterial dispersion in porous media and the biodegradation of heterogeneously contaminated scenarios.

Numerical Study of the Volcano Effect in Chemotactic Aggregation Based on a Kinetic Transport Equation with Non-instantaneous Tumbling.

Aggregation of chemotactic bacteria under a unimodal distribution of chemical cues was investigated by Monte Carlo (MC) simulation based on a kinetic transport equation, which considers an internal adaptation dynamics as well as a finite tumbling duration. It was found that there exist two different regimes of the adaptation time, between which the effect of the adaptation time on the aggregation behavior is reversed; that is, when the adaptation time is as small as the running duration, the aggregation becomes increasingly steeper as the adaptation time increases, while, when the adaptation time is as large as the diffusion time of the population density, the aggregation becomes more diffusive as the adaptation time increases. Moreover, the aggregation profile becomes bimodal (volcano) at the large adaptation-time regime when the tumbling duration is sufficiently large while it is always unimodal at the small adaptation-time regime. A remarkable result of this study is the identification of the parameter regime and scaling for the volcano effect. That is, by comparing the results of MC simulations to the continuum-limit models obtained at each of the small and large adaptation-time scalings, it is clarified that the volcano effect arises due to the coupling of diffusion, adaptation, and finite tumbling duration, which occurs at the large adaptation-time scaling.

Escherichia coli chemotaxis to competing stimuli in a microfluidic device with a constant gradient.

In natural systems bacteria are exposed to many chemical stimulants; some attract chemotactic bacteria as they promote survival, while others repel bacteria because they inhibit survival. When faced with a mixture of chemoeffectors, it is not obvious which direction the population will migrate. Predicting this direction requires an understanding of how bacteria process information about their surroundings. We used a multiscale mathematical model to relate molecular level details of their two-component signaling system to the probability that an individual cell changes its swimming direction to the chemotactic velocity of a bacterial population. We used a microfluidic device designed to maintain a constant chemical gradient to compare model predictions to experimental observations. We obtained parameter values for the multiscale model of Escherichia coli chemotaxis to individual stimuli, α-methylaspartate and nickel ion, separately. Then without any additional fitting parameters, we predicted bacteria response to chemoeffector mixtures. Migration of E. coli toward α-methylaspartate was modulated by adding increasing concentrations of nickel ion. Thus, the migration direction was controlled by the relative concentrations of competing chemoeffectors in a predictable way. This study demonstrated the utility of a multiscale model to predict the migration direction of bacteria in the presence of competing chemoeffectors.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Numerical Simulation of the Enrichment of Chemotactic Bacteria in Oil-Water Two-Phase Transfer Fields of Heterogeneous Porous Media

Oil pollution in soil-groundwater systems is difficult to remove, and a large amount of residual oil is trapped in the low permeable layer of the heterogeneous aquifer. Aromatic hydrocarbons in oil have high toxicity and low solubility in water, which are harmful to the ecological environment. Chemotactic degrading bacteria can perceive the concentration gradient of non-aqueous phase liquid (NAPL) pollutants in the groundwater environment, and enrich and proliferate around the pollutants, thus achieving a more efficient and thorough remediation effect. However, the existing theoretical models are relatively simple. The physical fields of oil–water two-phase flow and oil-phase solute convection and diffusion in water are not coupled, which further restricts the accuracy of studies on bacterial chemotaxis to NAPL. In this study, geometric models based on the actual microfluidic experimental study were constructed. Based on the phase field model, diffusion convection equation and chemotaxis velocity equation, the effects of heterogeneity of porous media, wall wettability and groundwater flow rate on the residual oil and the concentration distribution of chemotaxis bacteria were studied. Under all of the simulation conditions, the residual oil in the high permeable area was significantly lower than that in the low permeable area, and the wall hydrophilicity enhanced the water flooding effect. Chemotactic bacteria could react to the concentration gradient of pollutants dissolved into water in the oil phase, and enrich near the oil–water interface with high concentration of NAPL, and the density of chemotactic bacteria at the oil–water interface can be up to 1.8–2 times higher than that in the water phase at flow rates from 1.13 to 6.78 m/d.

Bacterial Growth, Communication, and Guided Chemotaxis in 3D-Bioprinted Hydrogel Environments.

Bioprinting of engineered bacteria is of great interest for applications of synthetic biology in the context of living biomaterials, but so far, only a few viable approaches are available for the printing of gels hosting live Escherichia coli bacteria. Here, we develop a gentle extrusion-based bioprinting method based on an inexpensive alginate/agarose ink mixture that enables printing of E. coli into three-dimensional hydrogel structures up to 10 mm in height. We first characterize the rheological properties of the gel ink and then study the growth of the bacteria inside printed structures. We show that the maturation of fluorescent proteins deep within the printed structures can be facilitated by the addition of a calcium peroxide-based oxygen generation system. We then utilize the bioprinter to control different types of interactions between bacteria that depend on their spatial position. We next show quorum-sensing-based chemical communication between the engineered sender and receiver bacteria placed at different positions inside the bioprinted structure and finally demonstrate the fabrication of barrier structures defined by nonmotile bacteria that can guide the movement of chemotactic bacteria inside a gel. We anticipate that a combination of 3D bioprinting and synthetic biological approaches will lead to the development of living biomaterials containing engineered bacteria as dynamic functional units.

Formation, collective motion, and merging of macroscopic bacterial aggregates.

Chemotactic bacteria form emergent spatial patterns of variable cell density within cultures that are initially spatially uniform. These patterns are the result of chemical gradients that are created from the directed movement and metabolic activity of billions of cells. A recent study on pattern formation in wild bacterial isolates has revealed unique collective behaviors of the bacteria Enterobacter cloacae. As in other bacterial species, Enterobacter cloacae form macroscopic aggregates. Once formed, these bacterial clusters can migrate several millimeters, sometimes resulting in the merging of two or more clusters. To better understand these phenomena, we examine the formation and dynamics of thousands of bacterial clusters that form within a 22 cm square culture dish filled with soft agar over two days. At the macroscale, the aggregates display spatial order at short length scales, and the migration of cell clusters is superdiffusive, with a merging acceleration that is correlated with aggregate size. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. The collective movement of the aggregates is the result of an asymmetric flux of bacteria at the boundary. An agent-based model is developed to examine how these phenomena are the result of both chemotactic movement and a change in motility at high cell density. These results identify and characterize a new mechanism for collective bacterial motility driven by a transient, density-dependent change in motility.

Transport of chemotactic bacteria in granular media with randomly distributed chemoattractant-containing NAPL ganglia: Modeling and simulation

Chemotaxis is the biased movement of bacteria upon sensing chemical gradients, which can facilitate bioremediation of nonaqueous phase liquids (NAPLs) by transporting oil-degrading bacteria more efficiently to contaminants in groundwater aquifers. Transport phenomena of chemotactic bacteria in porous media can be described within the context of a convection-dispersion equation (CDE) that includes an additional convection-like chemotactic velocity. In this paper, we present a novel modification of a previously reported CDE by including a single first-order kinetic term which can differentiate bacterial sorption on porous matrix and chemoattractant-containing NAPL ganglia. Our model was solved numerically using a finite-element scheme to compute bacterial transport in granular media at a continuum level and also captured chemotaxis to discrete, randomly distributed NAPL ganglia of chemoattractant sources. Simulation results revealed the influence of oil ganglia on bacterial transport. It was found that chemotactic bacteria exhibited localized hotspots near NAPL ganglia because of chemotaxis toward and sorption on oil surfaces. The presence of oil ganglia reduced recovery of chemotactic bacteria by 71% and nonchemotactic bacteria by 44%, which accompanied enhanced retention inside the column. Model results suggested that chemotactic bacteria can locate NAPL and thereby sorb on surfaces more efficiently, which may overcome the limited bioavailability of contaminants dissolved in NAPLs. Simulated outputs demonstrated good agreement with experimental data in literature. Our model provides insight into the impact of chemotaxis and interaction with oil-phase chemoattractant sources on bacterial transport in porous media.