A cell membrane can be considered a liquid-phase plane in which lipids and proteins theoretically are free to diffuse. Numerous reports, however, describe retarded diffusion of membrane proteins in animal cells. This anomalous diffusion results from a combination of structuring factors including protein-protein interactions, cytoskeleton corralling, and lipid organization into microdomains. In plant cells, plasma-membrane (PM) proteins have been described as relatively immobile, but the control mechanisms that structure the PM have not been studied. Here, we use fluorescence recovery after photobleaching to estimate mobility of a set of minimal PM proteins. These proteins consist only of a PM-anchoring domain fused to a fluorescent protein, but their mobilities remained limited, as is the case for many full-length proteins. Neither the cytoskeleton nor membrane microdomain structure was involved in constraining the diffusion of these proteins. The cell wall, however, was shown to have a crucial role in immobilizing PM proteins. In addition, by single-molecule fluorescence imaging we confirmed that the pattern of cellulose deposition in the cell wall affects the trajectory and speed of PM protein diffusion. Regulation of PM protein dynamics by the plant cell wall can be interpreted as a mechanism for regulating protein interactions in processes such as trafficking and signal transduction.

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We analyzed the dynamics of the earliest T cell response to SARS-COV-2. A wave of TCRs strongly but transiently expand during infection, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Most epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains, but not with circulating human coronaviruses. Many expanding CDR3s were also present at high precursor frequency in pre-pandemic TCR repertoires. A similar set of early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the pre-infection naïve repertoire. High frequency naïve precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.

Adaptive immunity recognises and responds to tumours, although they are part of the immunological 'self'. T cells, both CD4+ and CD8+ play a key role in the process, and the specific set of receptors which recognise tumour antigens therefore has the potential to provide prognostic biomarkers for tracking tumour growth after cancer therapy, including immunotherapy. Most published data on the T cell repertoire continues to rely on commercial proprietary methods, which often do not allow access to the raw data, and are difficult to validate. We describe an open-source protocol for amplifying, sequencing and analysing T cell receptors which is economical, robust, sensitive and versatile. The key experimental step is the ligation of a single stranded oligonucleotide to the 3' end of the T cell receptor cDNA, which allows easy amplification of all possible rearrangements using only a single set of primers per locus, while simultaneously introducing a unique molecular identifier to label each starting cDNA molecule. After sequencing, this molecular identifier can be used to correct both sequence errors and the effects of differential PCR amplification efficiency, thus producing a more accurate measure of the true T cell receptor frequency within the sample. Samples are then tagged with unique pairs of indices, facilitating robotic scale-up and significantly reducing cross-sample contamination from index hopping. This method has been applied to the analysis of tumour infiltrating lymphocytes and matched peripheral blood samples from patients with a variety of solid tumours.

Genomic analysis of the T-cell receptor (TCR) reveals the strength, breadth and clonal dynamics of the adaptive immune response to pathogens or cancer. The diversity of the TCR repertoire, however, means that sequencing is technically challenging, particularly for samples with low quality, degraded nucleic acids. Here, we have developed and validated FUME-TCRseq, a robust and sensitive RNA-based TCR sequencing methodology that is suitable for formalin-fixed paraffin-embedded samples and low amounts of input material. FUME-TCRseq incorporates unique molecular identifiers into each molecule of cDNA, allowing correction for sequencing errors and PCR bias. We used RNA extracted from colorectal and head and neck cancers to benchmark the accuracy and sensitivity of FUME-TCRseq against existing methods, and found excellent concordance between the datasets. Furthermore, FUME-TCRseq detected more clonotypes than a commercial RNA-based alternative, with shorter library preparation time and significantly lower cost. To demonstrate the utility of the methodology we performed spatially-resolved FUME-TCRseq of colorectal cancers using macrodissected archival samples, revealing the shifting T-cell landscapes at the transition to an invasive phenotype, and between tumour subclones containing distinct driver alterations. In summary, FUME-TCRseq represents an accurate, sensitive and low-cost tool for the characterisation of T-cell repertoires, particularly in samples with low quality RNA that have not been accessible using existing methodology.