Biology subjects

Tjandra, K. C.

Publications and source records attributed to Tjandra, K. C..

4 recordsLinked to original sources

bioRxiv2023

Rapid molecular phenotypic antimicrobial susceptibility test for Neisseria gonorrhoeae based on propidium monoazide viability PCR

Neisseria gonorrhoeae (NG) is an urgent threat to antimicrobial resistance (AMR) worldwide. NG has acquired rapid resistance to all previously recommended treatments leaving ceftriaxone monotherapy as the first and last line of therapy for uncomplicated NG. The ability to rapidly determine susceptibility, which is currently nonexistent for NG, has been proposed as a strategy to preserve ceftriaxone by using alternative treatments. Herein, we used a DNA-intercalating dye in combination with NG-specific primers/probes to generate qPCR cycle threshold (Ct) values at different concentrations of 2 NG-relevant antimicrobials. Our proof of concept dual-antimicrobial logistic regression model based on the differential Ct measurements achieved an AUC of 0.93 with a categorical agreement for susceptibility of 84.6%. When surveying the performance against each antimicrobial separately, the model predicted 90% and 75% susceptible and resistant strains respectively to ceftriaxone and 66.7% and 83.3% susceptible and resistant strains respectively to ciprofloxacin. We further validated the model against the individual replicates and determined the accuracy of the model in classifying susceptibility agnostic of the inoculum size. We demonstrated a novel PCR-based approach to determine phenotypic ciprofloxacin and ceftriaxone susceptibility information for NG with reasonable accuracy in under 30 min, a significant improvement compared to the conventional method which takes 3 days. Table of Content Graphic O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

microbiology↗

bioRxiv2022

MorphoAST: A Machine Learning Workflow for Sub-Doubling Time Single Cell Antimicrobial Susceptibility Testing

Multidrug-resistant Enterobacteriaceae are among the most urgent global public health threats associated with various life-threatening infections. In the absence of a rapid method to identify antimicrobial susceptibility, empirical use of broad-spectrum antimicrobials such as carbapenem monotherapy has led to the spread of resistant organisms. Rapid determination of antimicrobial resistance is urgently needed to overcome this issue. By capturing dynamic single-cell morphological features of over thirty-nine thousand cells from nineteen strains of Klebsiella pneumoniae, we evaluated strategies based on time and concentration differentials for classifying its susceptibility to a commonly used carbapenem, meropenem, and predicting their minimum inhibitory concentrations (MIC). We report morphometric antimicrobial susceptibility testing (MorphoAST), an image-based machine learning workflow, for rapid determination of antimicrobial susceptibility by single-cell morphological analysis within sub-doubling time. We demonstrated that our algorithm has the ability to predict MIC/antimicrobial susceptibility in a fraction of the bacterial doubling time (<50 min.). The classifiers achieved as high as 97% accuracy in 20 minutes (two-fifths of the doubling time) and reached over 99% accuracy within 50 minutes (one doubling time) in predicting the antimicrobial response. A regression model based on the concentration differential of individual cells from nineteen strains predicted the MIC with 100% categorical agreement and essential agreement for seven unseen strains, including two clinical samples from patients with urinary tract infections with different responsiveness to meropenem. The expansion of this innovation to other drug-bug combinations could have significant implications for future development of rapid antimicrobial susceptibility testing.

microbiology↗

bioRxiv2022

A 3D bioprintable hydrogel with tuneable stiffness for exploring cells encapsulated in matrices of differing stiffnesses

In vitro cell models have undergone a shift from 2D models on glass slides to 3D models that better reflect the native 3D microenvironment. 3D bioprinting promises to progress the field by allowing the high throughput production of reproducible cell-laden structures with high fidelity. As this technology is relatively new, the current stiffness range of printable matrices surrounding the cells that mimics the extracellular matrix environment remains limited. The work presented here aims to expand the range of stiffnesses by utilising a 4-armed polyethylene glycol with maleimide functionalised arms. The complementary crosslinkers comprised a matrix metalloprotease (MMP)-degradable peptide and a 4-armed thiolated polymer which were adjusted in ratio to tune the stiffness. The modularity of this system allows for a simple method of controlling stiffness and the addition of biological motifs. The application of this system in drop-on-demand printing is validated in this work using MCF-7 cells which were monitored for viability and proliferation. This study shows the potential of this system for the high-throughput investigation of the effects of stiffness and biological motif compositions in relation to cell behaviours.

cell biology↗

bioRxiv2021

A covalently crosslinked bioink for multi-materials drop-on-demand 3D bioprinting of three-dimensional cell cultures

In vitro three-dimensional (3D) cell models have been accepted to better recapitulate aspects of in vivo organ environment than 2D cell culture. Currently, the production of these complex in vitro 3D cell models with multiple cell types and microenvironments remains challenging and prone to human error. Here we report a versatile bioink comprised of a 4-arm PEG based polymer with distal maleimide derivatives as the main ink component and a bis-thiol species as the activator that crosslinks the polymer to form the hydrogel in less than a second. The rapid gelation makes the polymer system compatible with 3D bioprinting. The ink is combined with a drop-on-demand 3D bioprinting platform consisting of eight independently addressable nozzles and high-throughput printing logic for creating complex 3D cell culture models. The combination of multiple nozzles and fast printing logic enables the rapid preparation of many complex 3D structures comprising multiple hydrogel environments in the one structure in a standard 96-well plate format. The platform compatibility for biological applications was validated using pancreatic ductal adenocarcinoma cancer (PDAC) cells with their phenotypic responses controlled by tuning the hydrogel microenvironment.

bioengineering↗