Listening to life: Sonification for enhancing discovery in biological research.

Sonification, or the practice of generating sound from data, is a promising alternative or complement to data visualization for exploring research questions in the life sciences. Expressing or communicating data in the form of sound rather than graphs, tables, or renderings can provide a secondary information source for multitasking or remote monitoring purposes or make data accessible when visualizations cannot be used. While popular in astronomy, neuroscience, and geophysics as a technique for data exploration and communication, its potential in the biological and biotechnological sciences has not been fully explored. In this review, we introduce sonification as a concept, some examples of how sonification has been used to address areas of interest in biology, and the history of the technique. We then highlight a selection of biology-related publications that involve sonifications of DNA datasets and protein datasets, sonifications for data collection and interpretation, and sonifications aimed to improve science communication and accessibility. Through this review, we aim to show how sonification has been used both as a discovery tool and a communication tool and to inspire more life-science researchers to incorporate sonification into their own studies.

Spatial transcriptome-guided multi-scale framework connects P. aeruginosa metabolic states to oxidative stress biofilm microenvironment.

With the generation of spatially resolved transcriptomics of microbial biofilms, computational tools can be used to integrate this data to elucidate the multi-scale mechanisms controlling heterogeneous biofilm metabolism. This work presents a Multi-scale model of Metabolism In Cellular Systems (MiMICS) which is a computational framework that couples a genome-scale metabolic network reconstruction (GENRE) with Hybrid Automata Library (HAL), an existing agent-based model and reaction-diffusion model platform. A key feature of MiMICS is the ability to incorporate multiple -omics-guided metabolic models, which can represent unique metabolic states that yield different metabolic parameter values passed to the extracellular models. We used MiMICS to simulate Pseudomonas aeruginosa regulation of denitrification and oxidative stress metabolism in hypoxic and nitric oxide (NO) biofilm microenvironments. Integration of P. aeruginosa PA14 biofilm spatial transcriptomic data into a P. aeruginosa PA14 GENRE generated four PA14 metabolic model states that were input into MiMICS. Characteristic of aerobic, denitrification, and oxidative stress metabolism, the four metabolic model states predicted different oxygen, nitrate, and NO exchange fluxes that were passed as inputs to update the agent's local metabolite concentrations in the extracellular reaction-diffusion model. Individual bacterial agents chose a PA14 metabolic model state based on a combination of stochastic rules, and agents sensing local oxygen and NO. Transcriptome-guided MiMICS predictions suggested microscale denitrification and oxidative stress metabolic heterogeneity emerged due to local variability in the NO biofilm microenvironment. MiMICS accurately predicted the biofilm's spatial relationships between denitrification, oxidative stress, and central carbon metabolism. As simulated cells responded to extracellular NO, MiMICS revealed dynamics of cell populations heterogeneously upregulating reactions in the denitrification pathway, which may function to maintain NO levels within non-toxic ranges. We demonstrated that MiMICS is a valuable computational tool to incorporate multiple -omics-guided metabolic models to mechanistically map heterogeneous microbial metabolic states to the biofilm microenvironment.

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.

Chemorepellent-Loaded Nanocarriers Promote Localized Interference of Escherichia coli Transport to Inhibit Biofilm Formation.

To mitigate antimicrobial resistance, we developed polymeric nanocarrier delivery of the chemorepellent signaling agent, nickel, to interfere with Escherichia coli transport to a surface, an incipient biofilm formation stage. The dynamics of nickel nanocarrier (Ni NC) chemorepellent release and induced chemorepellent response required to effectively modulate bacterial transport for biofilm prevention were characterized in this work. Ni NCs were fabricated with the established Flash NanoPrecipitation method. NC size was characterized with dynamic light scattering. Measured with a zincon monosodium salt colorimetric assay, NC nickel release was pH-dependent, with 62.5% of total encapsulated nickel released at pH 7 within 0-15 min, competitive with rapid E. coli transport to the surface. Confocal laser scanning microscopy of E. coli (GFP-expressing) biofilm growth dynamics on fluorescently labeled Ni NC coated glass coupled with a theoretical dynamical criterion probed the biofilm prevention outcomes of NC design. The Ni NC coating significantly reduced E. coli attachment compared to a soluble nickel coating and reduced E. coli biomass area by 61% compared to uncoated glass. A chemical-in-plug assay revealed Ni NCs induced a chemorepellent response in E. coli. A characteristic E. coli chemorepellent response was observed away from the Ni NC coated glass over 10 µm length scales effective to prevent incipient biofilm surface attachment. The dynamical criterion provided semiquantitative analysis of NC mechanisms to control biofilm and informed optimal chemorepellent release profiles to improve NC biofilm inhibition. This work is fundamental for dynamical informed design of biofilm-inhibiting chemorepellent-loaded NCs promising to mitigate the development of resistance and interfere with the transport of specific pathogens.

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.

A mathematical model for Escherichia coli chemotaxis to competing stimuli.

Chemotactic bacteria sense and respond to temporal and spatial gradients of chemical cues in their surroundings. This phenomenon plays a critical role in many microbial processes such as groundwater bioremediation, microbially enhanced oil recovery, nitrogen fixation in legumes, and pathogenesis of the disease. Chemical heterogeneity in these natural systems may produce numerous competing signals from various directions. Predicting the migration behavior of bacterial populations under such conditions is necessary for designing effective treatment schemes. In this study, experimental studies and mathematical models are reported for the chemotactic response of Escherichia coli to a combination of attractant (α-methylaspartate) and repellent (NiCl2 ), which bind to the same transmembrane receptor complex. The model describes the binding of chemoeffectors and phosphorylation of the kinase in the signal transduction mechanism. Chemotactic parameters of E. coli (signaling efficiency σ , stimuli sensitivity coefficient γ , and repellent sensitivity coefficient κ ) were determined by fitting the model with experimental results for individual stimuli. Interestingly, our model naturally identifies NiCl2 as a repellent for κ>1 . The model is capable of describing quantitatively the response to the individual attractant and repellent, and correctly predicts the change in direction of bacterial population migration for competing stimuli with a twofold increase in repellent concentration.

Chemotaxis Increases the Retention of Bacteria in Porous Media with Residual NAPL Entrapment.

Chemotaxis has the potential to decrease the persistence of nonaqueous phase liquid (NAPL) contaminants in aquifers by allowing pollutant-degrading bacteria to move toward sources of contamination and thus influence dissolution. This experimental study investigated the migratory response of chemotactic bacteria to a distribution of residual NAPL ganglia entrapped within a laboratory-scale sand column under continuous-flow at a superficial velocity of 0.05 cm/min. Naphthalene dissolved in a model NAPL 2,2,4,4,6,8,8-heptamethylnonane partitioned into the aqueous phase to create localized chemoattractant gradients throughout the column. A pulse mixture of equal concentrations of Pseudomonas putida G7, a strain chemotactic to naphthalene, and Pseudomonas putida G7 Y1, a nonchemotactic mutant, was introduced to the column and effluent bacterial concentrations were measured with time. Breakthrough curves (BTCs) for the two strains were noticeably different upon visual inspection. Differences in BTCs (compared to nonchemotactic controls) were quantified in terms of percent recovery and were statistically significant ( p < 0.01). Chemotaxis reduced percent recovery in the effluent by 45% thereby increasing the population of bacteria that were retained within the column in the vicinity of residual NAPL contaminants. An increase in flow rate to a superficial velocity of 0.25 cm/min did not diminish cell retention associated with the chemotactic effect.

Modeling Transport of Chemotactic Bacteria in Granular Media with Distributed Contaminant Sources.

Chemotaxis has the potential to improve bioremediation strategies by enhancing the transport of pollutant-degrading bacteria to the source of contamination, leading to increased pollutant accessibility and biodegradation. This computational study extends work reported previously in the literature to include predictions of chemotactic bacterial migration in response to multiple localized contaminant sources within porous media. An advection-dispersion model, in which chemotaxis was represented explicitly as an additional advection-like term, was employed to simulate the transport of bacteria within a sand-packed column containing a distribution of chemoattractant sources. Simulation results provided insight into attractant and bacterial distributions within the column. In particular, it was found that chemotactic bacteria exhibited a distinct biased migration toward contaminant sources that resulted in a 30% decrease in cell recovery, and concomitantly an enhanced retention within the sand column, compared to the nonchemotactic control. Model results were consistent with experimental observations. Parametric studies were conducted to provide insight into the influence of chemotaxis parameters on bacterial migration and cell percent recovery. The model results provide a better understanding of the effect of chemotaxis on bacterial transport in response to distributed contaminant sources.

An engineering design approach to systems biology.

Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

Self-Partitioned Droplet Array on Laser-Patterned Superhydrophilic Glass Surface for Wall-less Cell Arrays.

In this work, we report a novel method for the creation of superhydrophilic patterns on the surface of hydrophobically coated glass through CO2 laser cleaning. This mask-free approach requires no photolithography for the print of the features, and only a single-step surface pretreatment is needed. The laser-cleaned glass surface enables self-partitioning of liquid into droplet arrays with controllable, quantitative volumes. We further designed wall-less cell arrays for the mapping of culturing conditions and demonstrated the potential of this droplet-arraying method.

Chemotaxis Increases the Residence Time of Bacteria in Granular Media Containing Distributed Contaminant Sources.

The use of chemotactic bacteria in bioremediation has the potential to increase access to, and the biotransformation of, contaminant mass within the subsurface. This laboratory-scale study aimed to understand and quantify the influence of chemotaxis on the residence times of pollutant-degrading bacteria within homogeneous treatment zones. Focus was placed on a continuous-flow sand-packed column in which a uniform distribution of naphthalene crystals created distributed sources of dissolved-phase contaminant. A 10 mL pulse of Pseudomonas putida G7, which is chemotactic to naphthalene, and Pseudomonas putida G7 Y1, a nonchemotactic mutant strain, were simultaneously introduced into the sand-packed column at equal concentrations. Breakthrough curves obtained from experiments conducted with and without naphthalene were used to quantify the effect of chemotaxis on transport parameters. In the presence of the chemoattractant, longitudinal dispersion of PpG7 increased by a factor of 3, and percent recovery decreased by 43%. In contrast, PpG7 Y1 transport was not influenced by the presence of naphthalene. The results imply that pore-scale chemotaxis responses are evident at an interstitial velocity of 1.8 m/day, which is within the range of typical groundwater flow. Within the context of bioremediation, chemotaxis may work to enhance bacterial residence times in zones of contamination, thereby improving treatment.

Enhanced Retention of Chemotactic Bacteria in a Pore Network with Residual NAPL Contamination.

Nonaqueous-phase liquid (NAPL) contaminants are difficult to eliminate from natural aquifers due, in part, to the heterogeneous structure of the soil. Chemotaxis enhances the mixing of bacteria with contaminant sources in low-permeability regions, which may not be readily accessible by advection and dispersion alone. A microfluidic device was designed to mimic heterogeneous features of a contaminated groundwater aquifer. NAPL droplets (toluene) were trapped within a fine pore network, and bacteria were injected through a highly conductive adjacent macrochannel. Chemotactic bacteria (Pseudomonas putida F1) exhibited greater accumulation near the pore network at 0.5 m/day than both the nonchemotactic control and the chemotactic bacteria at a higher groundwater velocity of 5 m/day. Chemotactic bacteria accumulated in the vicinity of NAPL droplets, and the accumulation was 15% greater than a nonchemotactic mutant. Indirect evidence showed that chemotactic bacteria were retained within the contaminated low-permeability region longer than nonchemotactic bacteria at 0.25 m/day. This retention was diminished at 5 m/day. Numerical solutions of the bacterial-transport equations were consistent with the experimental results. Because toluene is degraded by P. putida F1, the accumulation of chemotactic bacteria around NAPL sources is expected to increase contaminant consumption and improve the efficiency of bioremediation.

Quantitative analysis of chemotaxis towards toluene by Pseudomonas putida in a convection-free microfluidic device.

Chemotaxis has been shown to be beneficial for the migration of soil-inhabiting bacteria towards industrial chemical pollutants, which they degrade. Many studies have demonstrated the importance of this microbial property under various circumstances; however, few quantitative analyses have been undertaken to measure the two essential parameters that characterize the chemotaxis of bioremediation bacteria: the chemotactic sensitivity coefficient χ(0) and the chemotactic receptor constant K(c). The main challenge to determine these parameters is that χ(0) and K(c) are coupled together in non-linear mathematical models used to evaluate them. In this study we developed a method to accurately measure these parameters for Pseudomonas putida in the presence of toluene, an important pollutant in groundwater contamination. Our approach uses a multilayer microfluidic device to expose bacteria to a convection-free linear chemical gradient of toluene that is stable over time. The bacterial distribution within the gradient is measured in terms of fluorescence intensity, and is then used to fit the parameters Kc and χ(0) with mathematical models. Critically, bacterial distributions under chemical gradients at two different concentrations were used to solve for both parameters independently. To validate the approach, the chemotaxis parameters of Escherichia coli strains towards α-methylaspartate were experimentally derived and were found to be consistent with published results from related work.

Impact of fluorochrome stains used to study bacterial transport in shallow aquifers on motility and chemotaxis of Pseudomonas species.

One of the most common methods of tracking movement of bacteria in groundwater environments involves a priori fluorescent staining. A major concern in using these stains to label bacteria in subsurface injection-and-recovery studies is the effect they may have on the bacterium's transport properties. Previous studies investigated the impact of fluorophores on bacterial surface properties (e.g. zeta potential). However, no previous study has looked at the impact of fluorescent staining on swimming speed and chemotaxis. It was found that DAPI lowered the mean population swimming speed of Pseudomonas putida F1 by 46% and Pseudomonas stutzeri by 55%. DAPI also inhibited the chemotaxis in both strains. The swimming speeds of P. putida F1 and P. stutzeri were diminished slightly by CFDA/SE, but not to a statistically significant extent. CFDA/SE had no effect on chemotaxis of either strain to acetate. SYBR(®) Gold had no effect on swimming speed or the chemotactic response to acetate for either strain. This research indicates that although DAPI may not affect sorption to grain surfaces, it adversely affects other potentially important transport properties such as swimming and chemotaxis. Consequently, bacterial transport studies conducted using DAPI are biased to nonchemotactic conditions and do not appear to be suitable for monitoring the effect of chemotaxis on bacterial transport in shallow aquifers.

Bacterial chemotaxis toward a NAPL source within a pore-scale microfluidic chamber.

Chemotaxis toward chemical pollutants provides a mechanism for bacteria to migrate to locations of high contamination, which may improve the effectiveness of bioremediation. A microfluidic device was designed to mimic the dissolution of an organic-phase contaminant from a single pore into a larger macropore representing a preferred pathway for microorganisms that are carried along by groundwater flow. The glass windows of the microfluidic device allowed direct image analysis of bacterial distributions within the vicinity of the organic contaminant. Concentrations of chemotactic bacteria P. putida F1 near the organic/aqueous interface were 25% greater than those of a nonchemotactic mutant in the vicinity of toluene for a fluid velocity of 0.5 m/d. For E. coli responding to phenol, the bacterial concentrations were 60% greater than the controls, also at a velocity of 0.5 m/d. Velocities in the macropore were varied over a range from 0.5 to 10 m/d, the lower end of which is typical of groundwater velocities. The accumulation of chemotactic bacteria near the NAPL chemoattractant source decreased as the fluid velocity increased. Good agreement between computer-based simulations, generated using reasonable values of the model parameters, and the experimental data for P. putida strains confirmed the contribution due to chemotaxis. The experimental data for E. coli required a larger chemotactic sensitivity coefficient than that for P. putida, which was consistent with parameter values reported in the literature.

Idling time of motile bacteria contributes to retardation and dispersion in sand porous medium.

The motility of microorganisms affects their transport in natural systems by altering their interactions with the solid phase of the soil matrix. To assess the effect of these interactions on transport parameters, a series of breakthrough curves (BTCs) for motile and nonmotile bacteria, including E. coli and P. putida species, were measured from a homogeneously packed sand column under three different interstitial velocities of 1 m/d, 5 m/d, and 10 m/d. BTCs for the nonmotile bacteria were nearly identical for all three flow rates, except that the recovery percentage at 1 m/d was reduced by 5% compared to the higher flow rates. In contrast, for the motile bacteria, the recovery percentages were not affected by flow rate, but their BTCs exhibited a higher degree of retardation and dispersion as the flow velocity decreased, which was consistent with increased idling times of the motile strains. The smooth-swimming mutant E. coli HCB437, which is unable to change its swimming direction after encountering the solid surfaces and thus has the largest idling time, also exhibited the greatest degree of retardation and dispersion. All of the experimental observations were compared to results from an advection-dispersion transport model with three fitting parameters: retardation factor (R), longitudinal dispersivity (α(L)), and attachment rate coefficient (k(att)). In addition, the single-collector efficiency (η0) and collision efficiency (α) were calculated according to the colloid filtration theory (CFT), and confirmed that motile bacteria had lower collision efficiencies than nonmotile bacteria. This is consistent with previously reported observations that motile bacteria can avoid attachment to a solid surface by their active swimming capabilities. By quantifying the effect of bacterial motility on various transport parameters, more robust fate and transport models can be developed for decision-making related to environmental remediation strategies and risk assessment.

Chemotaxis increases vertical migration and apparent transverse dispersion of bacteria in a bench-scale microcosm.

The success of in situ bioremediation is often limited by the inability to bring bacteria in contact with the pollutant, which they will degrade. A bench-scale model aquifer was used to evaluate the impact of chemotaxis on the migration of bacteria toward the source of a chemical pollutant. The model was packed with sand and aqueous media was pumped across horizontally, simulating groundwater flow in a homogenous aquifer. A vertical gradient in chemoattractant was created by either a continuous injection of sodium benzoate or a pulse injection of sodium acetate. A pulse of chemotactic Pseudomonas putida F1 or a non-chemotactic mutant of the same species was injected below the attractant. The eluent was sampled at the microcosm outlet to generate vertical concentration profiles of the bacteria and chemoattractant. Moment analysis was used to determine the center and variance of the bacterial profiles. The center of the chemotactic bacterial population was located at an average of 0.74 ± 0.07 cm closer to the level at which the chemoattractant was injected than its non-chemotactic mutant in benzoate experiments (P < 0.015) and 0.4 ± 0.2 cm closer in acetate experiments (P < 0.05). The transverse dispersivity of the chemotactic bacteria was 4 ± 1 × 10(-3) cm higher in benzoate experiments than the transverse dispersivity of the non-chemotactic mutant and 1 ± 2 × 10(-3) cm higher in acetate experiments. These results underscore the contribution of chemotaxis to improve transport of bacteria to contaminant sources, potentially enhancing the effectiveness of in situ bioremediation.

Quantitative analysis of transverse bacterial migration induced by chemotaxis in a packed column with structured physical heterogeneity.

A two-dimensional mathematical model was developed to simulate transport phenomena of chemotactic bacteria in a sand-packed column designed with structured physical heterogeneity in the presence of a localized chemical source. In contrast to mathematical models in previous research work, in which bacteria were typically treated as immobile colloids, this model incorporated a convective-like chemotaxis term to represent chemotactic migration. Consistency between experimental observation and model prediction supported the assertions that (1) dispersion-induced microbial transfer between adjacent conductive zones occurred at the interface and had little influence on bacterial transport in the bulk flow of the permeable layers and (2) the enhanced transverse bacterial migration in chemotactic experiments relative to nonchemotactic controls was mainly due to directed migration toward the chemical source zone. On the basis of parameter sensitivity analysis, chemotactic parameters determined in bulk aqueous fluid were adequate to predict the microbial transport in our intermediate-scale porous media system. Additionally, the analysis of adsorption coefficient values supported the observation of a previous study that microbial deposition to the surface of porous media might be decreased under the effect of chemoattractant gradients. By quantitatively describing bacterial transport and distribution in a heterogeneous system, this mathematical model serves to advance our understanding of chemotaxis and motility effects in granular media systems and provides insights for modeling microbial transport in in situ microbial processes.

Idling time of swimming bacteria near particulate surfaces contributes to apparent adsorption coefficients at the macroscopic scale under static conditions.

Static capillary assays were performed to observe the distribution of Escherichia coli and several mutant strains at the interface between an aqueous solution and a Gelrite particulate suspension, used as a model porous medium. Motile smooth-swimming mutant bacteria (E. coli HCB437) accumulated at the interface, but did not penetrate very far into the Gelrite suspension. Motile wild-type bacteria (E. coli HCB1) penetrated much further than the smooth-swimming mutant, but did not accumulate to the same extent at the interface. Nonmotile tumbly mutant bacteria (E. coli HCB359) did not accumulate or penetrate to a significant degree. Computer simulations using a Monte Carlo algorithm, with input parameters based on bacterial swimming properties in static bulk aqueous systems, appeared to underestimate the bacterial idling time associated with solid surfaces. To account for physicochemical, biological and geometrical influences, an additional component of the bacterial idling time was included. The third component of the idling time was further analyzed semiquantitatively with a 1-D population-scale transport model with first-order association (k(on)) and dissociation (k(off)) adsorption-like kinetics. Computer simulation results suggested that this additional bacterial idling time not only increased the magnitudes of k(on) and k(off), but also enhanced the ratio of k(on) to k(off). This further implies that motile bacteria may tend to accumulate at the boundaries of low-permeable regions in groundwater systems, which is beneficial for bioremediation of residual contamination that may not be accessible by conventional remediation approaches.

Transverse bacterial migration induced by chemotaxis in a packed column with structured physical heterogeneity.

The significance of chemotaxis in directing bacterial migration toward contaminants in natural porous media was investigated under groundwater flow conditions. A laboratory-scale column, with a coarse-grained sand core surrounded by a fine-grained annulus, was used to simulate natural aquifers with strata of different hydraulic conductivities. A chemoattractant source was placed along the central axis of the column to model contaminants trapped in the heterogeneous subsurface. Chemotactic bacterial strains, Escherichia coli HCB1 and Pseudomonas putida F1, introduced into the column by a pulse injection, were found to alter their transport behaviors under the influence of the attractant chemical emanating from the central source. For E. coil HCB1, approximately 18% more of the total population relative to the control without attractant exited the column from the coarse sand layer due to the chemotactic effects of alpha-methylaspartate under an average fluid velocity of 5.1 m/d. Although P. putida F1 demonstrated no observable changes in migration pathways with the model contaminant acetate under the same flow rate, when the flow rate was reduced to 1.9 m/d, approximately 6-10% of the population relative to the control migrated from the fine sand layer toward attractant into the coarse sand layer. Microbial transport properties were further quantified by a mathematical model to examine the significance of bacterial motility and chemotaxis under different hydrodynamic conditions, which suggested important considerations for strain selection and practical operation of bioremediation schemes.