Samuel G. Rodriques's research while affiliated with Massachusetts Institute of Technology and other places

... TAP-seq [84]), hybridization baits (e.g. HyPR-seq [87] or biotinylated hybridization baits [74]) or custom beads [88]. ...

... We found that overall normalized gene expression remained constant over the cell cycle while miRNA targeting events, as measured by global editing patterns, increased throughout the cell cycle from G1 to M (Fig. 3i). This is consistent with previous observations that miRNA repression is weakest in the G1 phase 42 , but the increase in editing could also represent accumulated miRNA targeting over the cell cycle that is then diluted by new transcription in the G1 phase 43,44 . While transcripts with longer half-lives tend to accumulate slightly more editing events than do shorter-lived transcripts ( Supplementary Fig. 9), both groups display similarly increased editing throughout the cell cycle ( Supplementary Fig. 10), lending some evidence to the former hypothesis that genuine increased miRNA repression is involved. ...

... Because TRIBE represents a proximity approach to editing, the location of the cis-editing sites correlates with the location of RBP binding, but does not provide the exact nucleotides for RBP binding as does CLIP. Additional applications of MS2-TRIBE are being developed; for instance, MS2based RNA editing within single cells (Rodriques et al., 2020) provides a way to interrogate mRNA age by assessing the increase of edits with time and may be used to determine how cis-editing sites evolve with changes in developmental state. ...

... Optimal stLearn performance is achieved, however, when tissue morphology information from an H&E image (or other stain) is also included. That said, even without such imaging data, e.g. as with Slide-seq 15 , MERFISH 14 , seqFISH 13 and sci-Space data 33 , stLearn is still able to accurately infer spatial trajectories and cell-cell interactions based on spatial data and gene expression information alone. ...

... As a workaround for these challenges, multiple groups have proposed protein fingerprinting, in which partial sequence information is used to generate a unique protein fingerprint. [16][17][18][19][20] By mapping this fingerprint against a reference database, a protein can be identified. Thus far, proof-of-concept studies for protein fingerprinting have been limited to small model peptides, 19,[21][22][23] as their feasibility for fulllength protein is often hampered by their resolution, throughput or experimental complexity. ...

... On top of these, a thin tissue section is placed, and the cellular mRNA hybridizes to the primers. After sequencing the cellular mRNA content, it can be mapped back in space to the original tissue, as well as analysed with classical clustering methods (Ståhl et al., 2016;Rodriques et al., 2019). Additional to these experimental methods, various computational approaches facilitate the spatial reconstruction of scRNA-seq data (Nitzan et al., 2019;Stuart et al., 2019;Kleshchevnikov et al., 2020). ...

... Photo-patterning of materials is widely used for top-down fabrication. [36,52,68,69,83,137,[141][142][143][144][145][146][147][148][149][150][151][152][153][154][155][156][157] We achieved light-triggered outof-equilibrium patterning of an SDN hydrogel comprising photo-responsive peptide-type and lipid-type hydrogelators by inducing reaction-diffusion and seed-driven fiber formation (Figure 12a). [83] This out-of-equilibrium patterning proceeds through the spatial condensation of peptide-type nanofibers in the photo-irradiated areas and concurrent nanofiber depletion in the nonirradiated areas. ...

... Using optics to observe changes in cell refractive index and birefringence during electrical excitation [34] has failed to materialise as mainstream techniques. Theoretical studies have explored the feasibility of optical fibre refractometry [35] and surface plasmon resonance has been reported for neural recording in chamber [36] and fibre tip [37] configurations, but several issues remain unaddressed, including refractometry sensor characterisation, poor signal resolution, and a means of calibrating the outputted signal to biopotentials. Here, we present a practical implementation and experimental validation of a sensing fluorophore-free optrode with properties suitable for electrophysiology and brain-machine interface applications based on photonic techniques. ...