Search

Step emulsification (SE), which generates droplets by a sharp change in confinement, has emerged as a potential alternative to flow-focusing technology. Water/dispersed phase is continuously pumped through a shallow inlet channel into a deep chamber pre-filled with the oil/continuous phase. The need for one or more pumps to maintain a continuous flow for droplet generation, and the consequent use of high sample volumes, limit this technique to research labs. Here, we report a pumpfree SE technique for rapid and high-throughput generation of monodisperse hydrogel (agarose) beads using µl sample volume. Instead of using syringe pumps, we sequentially pipetted oil and liquid agarose into a microfluidic SE device to generate between 20000 and 80000 agarose beads in ∼ 2 min. We also demonstrated the encapsulation of loop-mediated isothermal amplification mixture inside these beads at the time of their formation. Finally, using these beads as reaction chambers, we amplified nucleic acids fromP. falciparumand SARS-CoV-2 inside them. The pump-free operation, tiny sample volume, and high-throughput generation of droplets by SE make our technique suitable for point-of-care diagnostics.

We report a two-layer microfluidic device to study the combined effect of confinement and chemical gradient on the motility of wild typeE. coli. We track individualE. coliin 50μmand 10μmwide channels, with a channel height of 2.5μm, to generate quasi-2D conditions. We find that contrary to expectations, bacterial trajectories are super-diffusive even in absence of a chemical (glucose) gradient. The superdiffusive behaviour becomes more pronounced on introduction of a chemical gradient or on strengthening the lateral confinement. Runlength distributions for weak confinement in absence of chemical gradients follow an exponential distribution. Both confinement and chemoattraction induce deviations from this behaviour, with the runlength distributions approaching a power-law form under these conditions. Both confinement and chemoattraction suppress large angle tumbles as well. Our results suggest that wild-typeE. colimodulates both its runs and tumbles in a similar manner under physical confinement and chemical gradient.

Molecular self-assembly plays vital role in various biological functions. However, when aberrant molecules self-assemble to form large aggregates, it can give rise to various diseases. For example, the sickle cell disease and Alzheimer’s disease are caused by self-assembled hemoglobin fibers and amyloid plaques, respectively. Here we study the assembly kinetics of such fibers using kinetic Monte-Carlo simulation. We focus on the initial lag time of these highly stochastic processes, during which self-assembly is very slow. The lag time distributions turn out to be similar for two very different regimes of polymerization, namely, a) when polymerization is slow and depolymerization is fast, and b) the opposite case, when polymerization is fast and depolymerization is slow. Using temperature dependent on- and off-rates for hemoglobin fiber growth, reported in recent in-vitro experiments, we show that the mean lag time can exhibit non-monotonic behaviour with respect to change of temperature.

In sickle cell anemia patients, red blood cells (RBCs) are known to become sickle shaped and stiff under hypoxic conditions as a consequence of hemoglobin polymerization. While RBC shape can discriminate sickle blood from healthy, it has not been used until now as a sole biophysical marker to differentiate between homozygous (disease) and heterozygous (trait) sickle blood samples. Here, we establish a technique based on the differential response of disease and trait RBCs to chemically-induced hypoxia to distinguish between these samples for the first time. By comparing the RBC shape distributions in blood treated with high and low concentrations of the hypoxia-inducing agent, we correctly identify 35 unknown blood samples as healthy, sickle cell disease or trait. Finally, we demonstrate our image-based classification technique with a portable smartphone microscope and a disposable microfluidic chip as a prospective point-of-care device enabling fast and confirmed diagnosis of sickle cell anemia. Significance statement Red blood cells (RBCs) of individuals with sickle cell anemia exhibit characteristic shapes in low oxygen environments. The shape of a sickle RBC is determined by its hemoglobin content and how fast oxygen is removed from its surroundings. We report a technique to distinguish between sickle cell carriers and individuals with sickle cell anemia within an hour by treating whole blood with a chemical that removes oxygen, imaging the blood sample inside a microfluidic chamber using a smartphone microscope and finally comparing the shapes of the sickle cells using a classification scheme. We demonstrate the proof of concept of a biophysical test based on the analysis of RBC shapes for point-of-care diagnosis of sickle cell disease in low resource settings.

We report a microfluidic device to determine the shear elastic modulus and the Young’s modulus of red blood cells (RBCs). Our device consists of a single channel opening into a funnel, with a semi-circular obstacle placed at the mouth of the funnel. As a RBC passes the obstacle, it deflects from its original path. Using populations of artificially-stiffened RBCs, we show that the stiffer RBCs deflect more compared to the normal RBCs. We use calibration curves obtained from numerical simulations to map a trajectory of each RBC to its elastic constants. Our estimates of the shear elastic modulus and the Young’s modulus of normal RBCs are within the same range of values reported in the literature using AFM, optical tweezers and micropipette measurements. We also estimate indirectly the elongation index of normal and artificially hardened RBCs from their tracks, without any direct observation of their shapes. Finally, we sort a mixed population of RBCs based on their deformability alone. Our device could potentially be further miniaturized to sort and obtain the elastic constants of nanoscale objects, whose shape change is difficult to monitor by optical microscopy.

Developing sensors in the domains of food safety, soil analysis, water quality monitoring and healthcare often requires distinguishing between different species of bacteria. The most rapid, sensitive and specific method to identify bacteria is by analysing their DNA sequence, which comprises of disinfection and lysis of bacterial cells, amplification of the isolated DNA and detection of the amplified sequence. Seamless integration of these assays on a paper substrate remains a big challenge in paperfluidic nucleic acid analyis. Combining lysis and isothermal amplification in a single reaction step is difficult because the porosity of paper and the presence of cell debris following lysis reduces the efficiency of DNA amplification. On the other hand, extracting and purifying the DNA after lysis to improve the amplification efficiency involves addition of chemical reagents, one or more wash steps and manual intervention. This problem is even more complex for mycobacteria as its thick cell wall structure impedes lysis and the high GC-content of the genome requires careful optimization of enzymatic denaturation during isothermal amplification. Here we successfully combine thermal lysis and loop-mediated isothermal amplification (LAMP) into a single reaction step on paper without the need for any intermediate intervention. We demonstrate our integrated assay by amplifying DNA from 100 CFU/mL ofEscherichia coli(MG1655) andMycobacterium smegmatis(mc2155) cells in 30 min on a paper substrate. We also confirm thatE. coliandM. smegmatiscan be completely disinfected on paper by heating at 60 °C for 5 min and 15 min respectively, making this assay safe and suitable for incorporation into diverse paperfluidic sensors for field use.Electronic Supplementary Information (ESI) is available.

Understanding the regulatory landscape of human cells requires the integration of genomic and epigenomic maps, capturing combinatorial levels of cell type-specific and invariant activity states.Here, we segmented whole-genome bisulfite sequencing-derived methylomes into consecutive blocks of co-methylation (COMETs) to obtain spatial variation patterns of DNA methylation (DNAm oscillations) integrated with histone modifications and promoter-enhancer interactions derived from promoter capture Hi-C (PCHi-C) sequencing of the same purified blood cells.Mapping DNAm oscillations onto regulatory genome annotation revealed that enhancers are enriched for DNAm hyper-oscillations (>30-fold), where multiple machine learning models support DNAm as predictive of enhancer location. Based on this analysis, we report overall predictive power of 99% for DNAm oscillations, 77.3% for DNaseI, 41% for CGIs, 20% for UMRs and 0% for LMRs, demonstrating the power of DNAm oscillations over other methods for enhancer prediction. Methylomes of activated and non-activated CD4+ T cells indicate that DNAm oscillations exist in both states irrespective of activation; hence they can be used to determine the location of latent enhancers.Our approach advances the identification of tissue-specific regulatory elements and outperforms previous approaches defining enhancer classes based on DNA methylation.