bioRxiv Science⌕ Search

Biology subjects

Buschmann, L.

Publications and source records attributed to Buschmann, L..

2 recordsLinked to original sources

A Framework for NGN1-Induced Sensory Neuron Differentiation for Disease Modelling and Drug Screening

Background: Neuropathic pain is a burdensome, difficult-to-treat, and highly heterogeneous condition with limited therapeutic options, underscoring the need for robust and reproducible human disease models. Human induced pluripotent stem cell (iPSC)-derived sensory neurons provide a promising platform for patient specific disease modelling and drug screening; however, their translational use is hampered by variability in differentiation efficiency, cellular composition, and functional maturation across protocols and cell lines. Methods: Here, we present a standardized and potentially scalable framework for NGN1 driven differentiation of human iPSCs into sensory neurons. Building on a previously published two step protocol (1), we systematically deconstructed and optimized each stage of differentiation across a large panel of genetically diverse iPSC lines. Results: We identified robust parameters for neural crest like cell (NCLC) generation, established a flow cytometry-based quality control strategy for NCLCs, and defined optimal combinations of seeding density and lentiviral multiplicity of infection to maximize sensory neuron progenitor yield. To improve culture homogeneity, we compared antimitotic selection strategies and demonstrated that tightly timed Ara-C treatment combined with low progenitor seeding density yields consistently pure sensory neuron cultures. We further evaluated maturation under physiologically relevant glucose conditions and performed a systematic review of media compositions to derive two defined maturation media. Morphological, immunocytochemical, transcriptomic, and electrophysiological analyses revealed that time in culture is a major determinant of maturation, while specific supplements such as prostaglandin E2; (PGE2) selectively enhance transcriptional signatures associated with nociceptor identity without substantially altering global network activity. Bulk RNA sequencing demonstrated broad expression of sensory neuron and pain related markers and gene programs across conditions, with long term maturation and PGE2; treatment showing the highest similarity to human dorsal root ganglion reference data. Functional assessment using multi electrode arrays enabled the detection of donor specific electrophysiological phenotypes, including reproducible hyperexcitability in small fiber neuropathy patient derived lines. Conclusions: This study establishes a modular, reproducible NGN1 based differentiation workflow with integrated quality checkpoints that accommodates iPSC line to line variability. The framework provides a practical foundation for translational sensory neuron research, patient specific disease modelling, and scalable drug screening applications.

neuroscience↗

Much ado about nothing: Modelling amino acid replacement with predicted protein structures

Substitution matrices like BLOSUM62 model the likelihood of replacement of amino acids in evolution. Substitution matrices are used in protein sequence alignment tasks. Since the introduction of BLOSUM62 over three decades ago, many matrices have been released. Yet, to date, no effort uses large amounts of 3D structures predicted by AlphaFold. Here, we define AFSM, the AlphaFold Substitution Matrix derived from over 20,000 predicted 3D structures following the BLOSUM methodology. We benchmark AFSM against BLOSUM62 and 16 other matrices on five tasks in multiple sequence alignment (MSA) and protein homology search. Our analysis surprisingly reveals that all matrices perform similarly. Only when there are few sequences in an MSA, then BLOSUM62 and AFSM perform better than using no matrix. This suggests that substitution matrices were most beneficial when there was little sequence data. We corroborate this argument by showing that embeddings, which are computed from billions of sequences, perform better than substitution matrices, when sequence data is sparse. Taken together, this suggests that structural data does not improve BLOSUM62. But increased sequence data makes extrapolation with substitution matrices obsolete. Nonetheless, BLOSUM62 continues to capture chemists intuition on amino acids by providing numerical values implicitly reflecting physicochemical properties, and it remains indispensable for direct comparison of two sequences.

bioinformatics↗