Biology subjects

Stojkovic, L.

Publications and source records attributed to Stojkovic, L..

2 recordsLinked to original sources

bioRxiv2026

MOSAIC: a longitudinal phenotypic clock to dissect organismal aging trajectories in C. elegans

Interventions that extend lifespan do not necessarily preserve healthspan, the portion of life spent in good health. This disconnect has intensified interest in biological aging clocks as quantitative proxies of organismal health. However, most existing clocks rely on invasive or endpoint measurements, providing static estimates that capture biological age at a single time point and offer limited insight into aging trajectories - the dynamic patterns through which physiological resilience and functional capacity change within individuals over time. Here we combine standardized, high-frequency imaging of individual Caenorhabditis elegans across the lifespan with machine learning to develop MOSAIC (Modular Organismal Signature of Aging In C. elegans), a non-invasive phenotypic clock that estimates biological age longitudinally at single-organism resolution. Leveraging [~]3750 animals, [~]230000 observations and 29 phenotypic features, MOSAIC predicts biological age with high accuracy and resolves organism-wide aging trajectories at high temporal resolution. Beyond age prediction, MOSAIC decomposes biological age into contributions from distinct physiological modules, enabling mechanistic interpretation of organismal decline. Applying MOSAIC to natural lifespan variation, dietary restriction, longevity mutants and pharmacological interventions reveals that lifespan extension can emerge through distinct, time-dependent phenotypic trajectories rather than a uniform slowing of aging. Interventions with similar effects on longevity produce divergent biological-age trajectories and distinct combinations of younger and older traits, highlighting context-dependent physiological trade-offs. MOSAIC provides a scalable, non-invasive framework to repeatedly quantify biological age across the lifespan and to compare interventions based on how they reshape aging trajectories.

bioinformatics↗

bioRxiv2024

Automated plasmid design for marker-free genome editing in budding yeast

The ease of genome editing has contributed to the popularity of budding yeast as a model organism. However, the palette of selectable markers is in principle limited as most can only be used once. Some markers such as URA3 and TRP1 can be recycled through counterselection. This permits seamless genome modification with pop-in/pop-out (PIPO), in which a DNA construct first integrates in the genome and, subsequently, homologous regions recombine and excise undesired sequences. Popular approaches for creating such constructs use oligonucleotides and polymerase chain reaction (PCR). The drawbacks are that long oligonucleotides are unstable, can form secondary structures that interfere with PCR, cannot be regenerated in a typical biological laboratory, and are only widely available for lengths less than about 120, which limits the homology and efficiency that can be attained. With the rapid reduction in price, synthesizing custom DNA sequences in specific plasmid backbones has become an appealing alternative. For designing plasmids for seamless PIPO gene tagging or deletion, there are a number of factors to consider. To create only the shortest DNA sequences necessary, avoid errors in manual design, specify the amount of homology desired, and customize restriction sites, we created the computational tool PIPOline. Using it, we tested the ratios of homology that improve pop-out efficiency when targeting the genes HTB2 or WHI5. We supply optimal PIPO plasmid sequences for tagging or deleting almost all S288C budding yeast open reading frames (ORFs). Finally, we demonstrate how the histone variant Htb2 marked with a red fluorescent protein can be used as a cell-cycle stage marker, alternative to superfolder GFP (sfGPF), reducing light toxicity. We expect PIPOline to streamline genome editing in budding yeast.

bioinformatics↗