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Lokshtanov, D.

Publications and source records attributed to Lokshtanov, D..

2 recordsLinked to original sources

Transgene-Free Ex Utero Derivation of A Human Post-Implantation Embryo Model Solely from Genetically Unmodified Naive PSCs

Our ability to study early human post-implantation development remains highly limited due to the ethical and technical challenges associated with intrauterine development of the human embryo after implantation. Despite the great progress made on human gastruloids, axioloids and in vitro cultured blastoids, such elegant models do not constitute an integrated Stem cell-derived Embryo Models (SEMs) that includes all the key extra-embryonic tissues of the early post-implantation human conceptus (e.g., hypoblast, yolk-sac, trophoblasts, amnion, and extraembryonic mesoderm), and thus, do not recapitulate post-implantation epiblast development within the context of these extra-embryonic compartments. Mouse naive pluripotent stem cells (PSCs) have recently been shown to give rise to embryonic and extra-embryonic stem cells capable of self-assembling into post-gastrulation mouse SEMs, while bypassing the blastocyst-like stage, and eventually initiating organogenesis ex utero. Here, we implement critical adaptations to extend these finding to humans, while using only genetically unmodified human naive PSCs, thus circumventing the need for ectopic expression of lineage promoting transgenes. Such integrated human SEMs recapitulate the organization of all known compartments of early post-implantation stage human embryos, including epiblast, hypoblast, extra-embryonic mesoderm, and trophoblast surrounding the latter layers. The organized human SEMs recapitulate key hallmarks of post-implantation stage embryogenesis up to 13-14 days post-fertilization (dpf, Carnegie stage 6a), such as bilaminar disk formation, epiblast lumenogenesis, amniogenesis, anterior-posterior symmetry breaking, PGC specification, primary and secondary yolk sac formation, and extra-embryonic mesoderm expansion that defines a chorionic cavity and a connective stalk. This new platform constitutes a tractable stem cell-based model for experimentally interrogating previously inaccessible windows of human peri- and early post-implantation development.

developmental biology↗

Syotti: Scalable Bait Design for DNA Enrichment

Bait-enriched sequencing is a relatively new sequencing protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ("baits") are designed, manufactured, and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. This effectively enriches the DNA for which the probes were designed. Most recently, Metsky et al. (Nature Biotech 2019) demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples. In this work, we formalize the problem of designing baits by defining the Minimum Bait Cover problem, which aims to find the smallest possible set of bait sequences that cover every position of a set of reference sequences under an approximate matching model. We show that the problem is NP-hard, and that it remains NP-hard under very restrictive assumptions. This indicates that no polynomial-time exact algorithm exists for the problem, and that the problem is intractable even for small and deceptively simple inputs. In light of this, we design an efficient heuristic that takes advantage of succinct data structures. We refer to our method as syotti. The running time of syotti shows linear scaling in practice, running at least an order of magnitude faster than state-of-the-art methods, including the recent method of Metsky et al. At the same time, our method produces bait sets that are smaller than the ones produced by the competing methods, while also leaving fewer positions uncovered. Lastly, we show that syotti requires only 25 minutes to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas the method of Metsky et al. shows clearly super-linear running time and fails to process even a subset of 8% of the data in 24 hours. Our implementation is publicly available at https://github.com/jnalanko/syotti.

bioinformatics↗