Dynamic Dosing Assay Relating Real-Time Respiration Responses of Staphylococcus aureus Biofilms to Changing Microchemical Conditions

Red blood cell classification in lensless single random phase encoding using convolutional neural networks

Rapid cell identification is achieved in a compact and field-portable system employing single random phase encoding to record opto-biological signatures of living biological cells of interest. The lensless, 3D-printed system uses a diffuser to encode the complex amplitude of the sample, then the encoded signal is recorded by a CMOS image sensor for classification. Removal of lenses in this 3D sensing system removes restrictions on the field of view, numerical aperture, and depth of field normally imposed by objective lenses in comparable microscopy systems to enable robust 3D capture of biological volumes. Opto-biological signatures for two classes of animal red blood cells, situated in a microfluidic device, are captured then input into a convolutional neural network for classification, wherein the AlexNet architecture, pretrained on the ImageNet database is used as the deep learning model. Video data was recorded of the opto-biological signatures for multiple samples, then each frame was treated as an input image to the network. The pre-trained network was fine-tuned and evaluated using a dataset of over 36,000 images. The results show improved performance in comparison to a previously studied Random Forest classification model using extracted statistical features from the opto-biological signatures. The system is further compared to and outperforms a similar shearing-based 3D digital holographic microscopy system for cell classification. In addition to improvements in classification performance, the use of convolutional neural networks in this work is further demonstrated to provide improved performance in the presence of noise. Red blood cell identification as presented here, may serve as a key step toward lensless pseudorandom phase encoding applications in rapid disease screening. To the best of our knowledge this is the first report of lensless cell identification in single random phase encoding using convolutional neural networks.

Transport and Retention Behaviors of Deformable Polyacrylamide Microspheres in Convergent-Divergent Microchannels

Knowledge of the transport and retention behaviors of soft deformable particles on the microscale is essential for the design, evaluation, and application of engineered particle materials in the fields of energy, environment, and sustainability. Emulated convergent-divergent microchannels were constructed and used to investigate the transport and retention behaviors of soft deformable polyacrylamide microspheres at various conditions. Five different types of transport and retention patterns, i.e., surface deposition, smooth passing, direct interception, deforming remigration, and rigid blockage, are observed. Flow resistance variation characteristics caused by different patterns were quantitatively analyzed. Effects of flow rate, pore-throat size, particle size, and injection concentration on transport and retention patterns have been studied, and transport and retention pattern maps are presented and discussed.

Adaptive Evolution of Escherichia coli to Ciprofloxacin in Controlled Stress Environments: Contrasting Patterns of Resistance in Spatially Varying versus Uniformly Mixed Concentration Conditions

A microfluidic gradient chamber (MGC) and a homogeneous batch culturing system were used to evaluate whether spatial concentration gradients of the antibiotic ciprofloxacin allow development of greater antibiotic resistance in Escherichia coli strain 307 (E. coli 307) compared to exclusively temporal concentration gradients, as indicated in an earlier study. A linear spatial gradient of ciprofloxacin and Luria-Bertani broth (LB) medium was established and maintained by diffusion over 5 days across a well array in the MGC, with relative concentrations along the gradient of 1.7-7.7× the original minimum inhibitory concentration (MIC_original). The E. coli biomass increased in wells with lower ciprofloxacin concentrations, and only a low level of resistance to ciprofloxacin was detected in the recovered cells (∼2× MIC_original). Homogeneous batch culture experiments were performed with the same temporal exposure history to ciprofloxacin concentration, the same and higher initial cell densities, and the same and higher nutrient (i.e., LB) concentrations as in the MGC. In all batch experiments, E. coli 307 developed higher ciprofloxacin resistance after exposure, ranging from 4 to 24× MIC_original in all replicates. Hence, these results suggest that the presence of spatial gradients appears to reduce the driving force for E. coli 307 adaptation to ciprofloxacin, which suggests that results from batch experiments may over predict the development of antibiotic resistance in natural environments.

Dynamic Sessile-Droplet Habitats for Controllable Cultivation of Bacterial Biofilm

Bacterial biofilms play essential roles in biogeochemical cycling, degradation of environmental pollutants, infection diseases, and maintenance of host health. The lack of quantitative methods for growing and characterizing biofilms remains a major challenge in understanding biofilm development. In this study, a dynamic sessile-droplet habitat is introduced, a simple method which cultivates biofilms on micropatterns with diameters of tens to hundreds of micrometers in a microfluidic channel. Nanoliter plugs are utilized, spaced by immiscible carrier oil to initiate and support the growth of an array of biofilms, anchored on and spatially confined to the micropatterns arranged on the bottom surface of the microchannel, while planktonic or dispersal cells are flushed away by shear force of aqueous plugs. The performance of the aforementioned method of cultivating biofilms is demonstrated by Pseudomonas aeruginosa PAO1 and its derived mutants, and quantitative antimicrobial susceptibility testing of PAO1 biofilms. This method could significantly eliminate corner effects, avoid microchannel clogging, and constrain the growth of biofilms for long-term observations. The controllable sessile droplet-based biofilm cultivation presented in this study should shed light on more quantitative and long-term studies of biofilms, and open new avenues for investigation of biofilm attachment, growth, expansion, and eradication.

A 3D-printed microbial cell culture platform with in situ PEGDA hydrogel barriers for differential substrate delivery

Additive manufacturing, or 3D-printing techniques have recently begun to enable simpler, faster, and cheaper production of millifluidic devices at resolutions approaching 100-200 μm. At this resolution, cell culture devices can be constructed that more accurately replicate natural environments compared with conventional culturing techniques. A number of microfluidics researchers have begun incorporating additive manufacturing into their work, using 3D-printed devices in a wide array of chemical, fluidic, and even some biological applications. Here, we describe a 3D-printed cell culture platform and demonstrate its use in culturing Pseudomonas putida KT2440 bacteria for 44 h under a differential substrate gradient. Polyethylene glycol diacrylate (PEGDA) hydrogel barriers are patterned in situ within a 3D-printed channel. Transport of the toluidine blue tracer dye through the hydrogel barriers is characterized. Nutrients and oxygen were delivered to cells in the culture region by diffusion through the PEGDA hydrogel barriers from adjacent media or saline perfusion channels. Expression of green fluorescent protein by P. putida KT2440 enabled real time visualization of cell density within the 3D-printed channel, and demonstrated cells were actively expressing protein over the course of the experiment. Cells were observed clustering near hydrogel barrier boundaries where fresh substrate and oxygen were being delivered via diffusive transport, but cells were unable to penetrate the barrier. The device described here provides a versatile and easy to implement platform for cell culture in readily controlled gradient microenvironments. By adjusting device geometry and hydrogel properties, this platform could be further customized for a wide variety of biological applications.

High-throughput dental biofilm growth analysis for multiparametric microenvironmental biochemical conditions using microfluidics

Dental biofilm formation is not only a precursor to tooth decay, but also induces more serious systematic health problems such as cardiovascular disease and diabetes. Understanding the conditions promoting colonization and subsequent biofilm development involving complex bacteria coaggregation is particularly important. In this paper, we report a high-throughput microfluidic 'artificial teeth' device offering controls of multiple microenvironmental factors (e.g. nutrients, growth factors, dissolved gases, and seeded cell populations) for quantitative characteristics of long-term dental bacteria growth and biofilm development. This 'artificial teeth' device contains multiple (up to 128) incubation chambers to perform parallel cultivation and analyses (e.g. biofilm thickness, viable-dead cell ratio, and spatial distribution of multiple bacterial species) of bacteria samples under a matrix of different combinations of microenvironmental factors, further revealing possible developmental mechanisms of dental biofilms. Specifically, we applied the 'artificial teeth' to investigate the growth of two key dental bacteria, Streptococci species and Fusobacterium nucleatum, in the biofilm under different dissolved gas conditions and sucrose concentrations. Together, this high-throughput microfluidic platform can provide extended applications for general biofilm research, including screening of the biofilm properties developing under combinations of specified growth parameters such as seeding bacteria populations, growth medium compositions, medium flow rates and dissolved gas levels.

Protist-facilitated particle transport using emulated soil micromodels

Microbial processes in the subsurface can be visualized directly using micromodels to emulate pore-scale geometries. Here, emulated soil micromodels were used to measure transport of fluorescent beads in the presence and absence of the soil ciliate Colpoda sp. under quiescent conditions. Beads alone or beads with protists were delivered to the input wells of replicate micromodels that contained three 20 mm(2) channels emulating a sandy loam microstructure. Bead abundance in microstructured channels was measured by direct counts of tiled confocal micrographs. For channels with protists, average bead abundances were approximately 320, 560, 710, 830, and 790 mm(-2) after 1, 2, 3, 5, and 10 days, respectively, versus 0, 0, 0.3, 7.8, and 45 mm(-2) without protists. Spatial and temporal patterns of bead abundance indicate that protist-facilitated transport is not a diffusive-type process but rather a function of more complex protist behaviors, including particle uptake and egestion and motility in a microstructured habitat. Protist-facilitated transport may enhance particle mixing in the soil subsurface and could someday be used for targeted delivery of nanoparticles, encapsulated chemicals, or bacteria for remediation and agriculture applications.