Biology subjects

Sanka, I.

Publications and source records attributed to Sanka, I..

5 recordsLinked to original sources

bioRxiv2026

A droplet-to-data workflow for antimicrobial screening of complex matrices

Screening plant extracts and other complex natural matrices for antibacterial activity is complicated by optical interference and population averaging in conventional bulk assays. Droplet-based assays mitigate interference while enabling high-throughput assessment of bacterial subpopulations. However, analyzing the resulting image data involves difficult image processing, classification, and interpretation. Here, we present a democratized workflow for antimicrobial screening in complex matrices that combines a polydisperse droplet-based assay with EasyFlow 2.0 (EF2), our updated droplet image analysis platform. EF2 offers stable containerized deployment, expanded polydisperse droplet support, automated thresholding and MIC estimation, LLM-assisted data exploration, and import of other software outputs such as CellProfiler (CP) measurements and CellProfiler Analyst (CPA) classification models. As proof of concept, we applied this workflow to assess the antibacterial and aggregation-modulating effects of chemically distinct extracts of Taraxacum officinale, Rhodiola rosea, and Lonicera caerulea against Escherichia coli. Extracts were chemically characterized by HPLC-MS and evaluated using both standard 96-well plate microdilution and droplet-based assays. In total, 27,059 droplets were segmented in CP, classified into four growth phenotypes using a CPA random forest model, and analyzed in EF2. The droplet-based assay reached minimal inhibitory concentration (MIC) at lower extract concentrations than 96-well plate microdilution and revealed extract-specific aggregation effects: L. caerulea reduced E. coli aggregation, whereas T. officinale did not. R. rosea reduced growth in the 96-well plate microdilution assay, but high concentrations caused droplet gelation that prevented droplet-based analysis, showing that sample components must be checked for compatibility with droplet formation. These results illustrate that the EF2-centered workflow supports rapid, automated MIC estimation through unsupervised thresholding when labels are unavailable, and four-class aggregation phenotyping when a CPA model is supplied. This workflow offers flexible, scalable screening, potentially extendable beyond plant extracts to other complex sample matrices.

microbiology↗

bioRxiv2024

High-throughput bacterial aggregation analysis in droplets

Microfluidic droplet platforms provide a rapid tool to study and capture bacterial aggregation in a well-controlled micro-environment, while image analysis presents an easily available technique to investigate droplet contents. However, the lack of standardised, well-documented methods and reliance on custom image analysis workflows limits wider adoption of the method and produces inconsistent, incomparable data on aggregation. We present a robust, cost-effective method using both mono- and polydisperse droplets and texture-based image analysis via an open-source software CellProfiler to assess bacterial aggregation. Compared to a manual droplet evaluation carried out by a human expert panel, textural characterisation achieves accuracy over 90% and more than 80% precision. Applying the pipeline, we found that suboptimal antibiotic concentrations can increase aggregation, whereas exposure to microplastic beads and metals reduces it. Overall, the developed pipeline offers high accuracy, easy setup, and broad applicability for bacterial aggregation.

bioinformatics↗

bioRxiv2021

EasyFlow: User-friendly Workflow for Image-based Droplet Analysis with Multipurpose Modules

Water-in-oil droplets allow researchers to perform massive experimental parallelization and high-throughput studies, such as single-cell experiments. However, the analysis of such vast arrays of droplets usually requires advanced expertise and sophisticated workflow tools, which limits the accessibility for wider user base in chemistry and biology. Thus, there is a need for more user-friendly tools for droplet analysis. In this article, we deliver a set of analytical pipelines for user-friendly analysis of typical scenarios in droplet-based experiments. We build the pipelines combining different open-source image-analysis software with the custom-developed data visualization tool "EasyFlow". Our pipelines are designed to be applicable for the typical experimental scenarios users encounter with droplets: i) mono- and polydisperse droplets, ii) brightfield and fluorescent images, iii) droplet and object detection, iv) signal profile of droplets and objects (e.g., fluorescence).

bioinformatics↗

bioRxiv2021

Investigation of Different Free Image Analysis Software for High-Throughput Droplet Detection

Droplet microfluidics has revealed innovative strategies in biology and chemistry. This advancement has delivered novel quantification methods, such as digital droplet polymerase chain reaction (ddPCR) and antibiotic heteroresistance analysis tool. For droplet analysis, researchers often use imaging techniques. Unfortunately, the analysis of images may require specific tools or programming skills to produce the expected results. In order to address the issue, we explore the potential use of standalone freely available software to detect droplets. We select four most popular software and classify them into instinctive and objective types based on their operation logic. We test and evaluate the softwares i) ability to detect droplets, ii) accuracy and precision, and iii) overall user-friendliness. In our experimental setting we find the objective type of software is better suited for droplet detection. The objective type of software also has simpler workflow or pipeline, especially aimed for non-experienced user. In our case, CellProfiler (CP) offers the most user-friendly experience for both single image and batch processing analysis.

bioinformatics↗

bioRxiv2019

CellProfiler: A fit tool for image analysis in droplet microfluidics

Droplet microfluidic assays are rapidly gaining popularity as the result of the ability to manipulate and monitor single biological molecules, individual cells or small populations of bacteria in pico- and nanoliter droplets, with high sensitivity, precision and accuracy in a high-throughput manner. Nonetheless, there is a demand for user-friendly and low-cost droplet analysis technology. In this article we meet this demand with free open-source software CellProfiler (CP). To illustrate the competence of CP as a droplet analysis tool, we show droplet digital quantification of viable fluorescent bacteria.

bioinformatics↗