Biology subjects

Tan, S. X.

Publications and source records attributed to Tan, S. X..

3 recordsLinked to original sources

bioRxiv2026

Layered phage therapy exploits capsule-loss escape and altered antibiotic susceptibility in CG23 hypervirulent Klebsiella pneumoniae

The rise of drug-resistant Klebsiella pneumoniae infections is prompting a re-evaluation of phage therapy as an alternative treatment. Phage therapy has achieved successful outcomes, yet important limitations persist, including the rapid emergence of phage resistance and the time required to source suitable phages. Combining multiple phages into a phage cocktail based on genetic diversity, morphology or distinct infection mechanisms is a common strategy to mitigate resistance. Phage pairing based on these criteria neither mitigates nor delays the emergence of resistance, using CG23 hypervirulent Klebsiella pneumoniae (hvKp) EC0675 as a model. In CG23 Kp strains, resistance arises through disruption of the capsular biosynthetic pathway, leading to capsule impairment and global cross-resistance to all capsule-active phages. Combining phages active against encapsulated wild-type bacteria with those active against capsule-deficient escape mutants can overcome this constraint, improving bacterial suppression in vitro and reducing bacterial burdens across multiple organs in a mouse systemic infection model. In parallel, phage-driven capsule loss increased susceptibility of hvKp EC0675 to selected antibiotics targeting the bacterial envelope or cell wall in vitro. These findings highlight the contribution of capsule-associated resistance to phage cross-resistance in the CG23 Kp strains examined, and support further evaluation of phage combinations targeting both wild-type bacteria and resistant derivatives, including their use alongside selected antibiotics, informing future clinical translation.

microbiology↗

bioRxiv2026

A chromosome-scale Plasmodium cynomolgi Berok genome reveals a distinct subtelomeric architecture and a highly diverged primate malaria lineage

Plasmodium cynomolgi is the closest relative of P. vivax and the primary experimental model for relapsing malaria, hypnozoite biology, and blood-stage drug susceptibility. Yet existing reference genomes remain fragmented, leaving structurally complex, AT-rich regions largely unresolved. We generated a chromosome-scale genome assembly for the K4-A7 cloned line of P. cynomolgi Berok by combining Hi-C chromosome conformation capture, Oxford Nanopore long reads, PacBio, and Illumina sequencing. The assembly spans 14 chromosomes plus mitochondrial and apicoplast genomes, with only seven unplaced minor contigs, the fewest for any non-P. falciparum Plasmodium genome, and an N50 of 3.06 Mb. Critically, this hybrid strategy resolved approximately 8 Mb of extremely AT-rich (~20% GC) sequence onto chromosomes 4, 8, and 13, anchoring what were previously unplaced or absent contigs into a continuous chromosomal framework. These subtelomere-like expansions (SLEs) constitute ~26.5% of the chromosomal genome and are enriched for PIR/VIR, STP1, variable surface antigen, and methyltransferase pseudogene families. Despite low gene density, SLE-encoded genes are transcriptionally active and show stage-specific expression across the erythrocytic cycle. Integrated lifecycle transcriptomics across 7,006 genes revealed a ~54-hour erythrocytic cycle with a "just-in-time" transcriptional cascade closely resembling that of P. vivax. Phylogenomic analyses and pairwise amino acid comparisons across more than 2,600 single-copy orthologs show that Berok forms a deeply diverged P. cynomolgi lineage, suggesting a distinct subspecies. This assembly establishes a high-resolution genomic foundation for comparative malaria biology, drug discovery, and the study of subtelomeric architecture, host adaptation, and lineage boundaries in primate Plasmodium.

microbiology↗

bioRxiv2025

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

cancer biology↗