An Optimised Protocol Harnessing Laser Capture Microdissection for Transcriptomic Analysis on Matched Primary and Metastatic Colorectal Tumours

The emerging role of the gut microbiota and its application in inflammatory bowel disease

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a complex disorder with an unknown cause. However, the dysbiosis of the gut microbiome has been found to play a role in IBD etiology, including exacerbated immune responses and defective intestinal barrier integrity. The gut microbiome can also be a potential biomarker for several diseases, including IBD. Currently, conventional treatments targeting pro-inflammatory cytokines and pathways in IBD-associated dysbiosis do not yield effective results. Other therapies that directly target the dysbiotic microbiome for effective outcomes are emerging. We review the role of the gut microbiome in health and IBD and its potential as a diagnostic, prognostic, and therapeutic target for IBD. This review also explores emerging therapeutic advancements that target gut microbiome-associated alterations in IBD, such as nanoparticle or encapsulation delivery, fecal microbiota transplantation, nutritional therapies, microbiome/probiotic engineering, phage therapy, mesenchymal stem cells (MSCs), gut proteins, and herbal formulas.

An optimized workflow for transcriptomic analysis from archival paraformaldehyde-fixed retinal tissues collected by laser capture microdissection

RNA sequencing (RNA-seq) coupled with laser capture microdissection (LCM) is a powerful tool for transcriptomic analysis in unfixed fresh-frozen tissues. Fixation of ocular tissues for immunohistochemistry commonly involves the use of paraformaldehyde (PFA) followed by embedding in Optimal Cutting Temperature (OCT) medium for long-term cryopreservation. However, the quality of RNA derived from such archival PFA-fixed/OCT-embedded samples is often compromised, limiting its suitability for transcriptomic studies. In this study, we aimed to develop a methodology to extract high-quality RNA from PFA-fixed canine eyes by utilizing LCM to isolate retinal tissue. We demonstrate the efficacy of an optimized LCM and RNA purification protocol for transcriptomic profiling of PFA-fixed retinal specimens. We compared four pairs of canine retinal tissues, where one eye was subjected to PFA-fixation prior to OCT embedding, while the contralateral eye was embedded fresh frozen (FF) in OCT without fixation. Since the RNA obtained from PFA-fixed retinas were contaminated with genomic DNA, we employed two rounds of DNase I treatment to obtain RNA suitable for RNA-seq. Notably, the quality of sequencing reads and gene sets identified from both PFA-fixed and FF tissues were nearly identical. In summary, our study introduces an optimized workflow for transcriptomic profiling from PFA-fixed archival retina. This refined methodology paves the way for improved transcriptomic analysis of preserved ocular tissue, bridging the gap between optimal sample preservation and high-quality RNA data acquisition.

Comparative transcriptomics reveals highly conserved regional programs between porcine and human colonic enteric nervous system

The porcine gut is increasingly regarded as a useful translational model. The enteric nervous system in the colon coordinates diverse functions. However, knowledge of the molecular profiling of porcine enteric nerve system and its similarity to that of human is still lacking. We identified the distinct transcriptional programs associated with functional characteristics between inner submucosal and myenteric ganglia in porcine proximal and distal colon using bulk RNA and single-cell RNA sequencing. Comparative transcriptomics of myenteric ganglia in corresponding colonic regions of pig and human revealed highly conserved programs in porcine proximal and distal colon, which explained >96% of their transcriptomic responses to vagal nerve stimulation, suggesting that porcine proximal and distal colon could serve as predictors in translational studies. The conserved programs specific for inflammatory modulation were displayed in pigs with vagal nerve stimulation. This study provides a valuable transcriptomic resource for understanding of human colonic functions and neuromodulation using porcine model.

Single-cell RNA-sequencing of retrieved human oocytes and eggs in clinical practice and for human ovarian cell atlasing

With the advancement of single-cell separation techniques and high-throughput sequencing platforms, single-cell RNA-sequencing (scRNA-seq) has emerged as a vital technology for understanding tissue and organ systems at cellular resolution. Through transcriptional analysis, it is possible to characterize unique or rare cell types, interpret their interactions, and reveal novel functional states or shifts in developmental stages. As such, this technology is uniquely suited for studying the cells within the human ovary. The ovary is a cellularly heterogeneous organ that houses follicles, the reproductive and endocrine unit that consists of an oocyte surrounded by hormone-producing support cells, as well as many other cell populations constituting stroma, vasculature, lymphatic, and immune components. Here we review studies that have utilized scRNA-seq technology to analyze cells from healthy human ovaries and discuss the single-cell isolation techniques used. We identified two overarching applications for scRNA-seq in the human ovary. The first applies this technology to investigate transcriptional differences in oocytes/eggs from patients undergoing in vitro fertilization treatments to ultimately improve clinical outcomes. The second utilizes scRNA-seq for the pursuit of creating a comprehensive single-cell atlas of the human ovary. The knowledge gained from these studies underscores the importance of scRNA-seq technologies in unlocking a new biological understanding of the human ovary.

Opioid Receptor Expression in Colorectal Cancer: A Nested Matched Case-Control Study

Background

There is growing interest in the possible effect of perioperative anesthetic management on the growth and spread of cancer. The impact of perioperative use of opioids on cancer recurrence remains controversial and an assessment cannot yet be established based on current publications. This study aimed to assess the differential expression of opioid receptors between healthy and tumor tissues in patients with stage II and III colorectal cancer undergoing elective surgery by immunohistochemistry (IHC).

Methods

Propensity-score matched case-control study nested in a retrospective cohort of patients with stage II or III colorectal. The primary endpoint was the difference in µ-opioid receptor (MOR) expression measured by IHC between tumor and healthy tissue in subject with or without recurrence. Secondary endpoints were to evaluate the differences in Opioid Growth Factor Receptor (OGFR), cyclic adenosine monophosphate (cAMP) production and protein kinase A (PKA) in the matched sample and from a from samples of colorectal cancer stored in the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression Project (GTEx).

Results

There was a significant difference in MOR receptor (median 3 [intequartile range IQR: 1-3] and 0 [IQR: 0-2], P<0.001) and OGFR receptor (median 6 [IQR: 5-6] and 2 [IQR: 1-2], P<0.001) in tumor and control tissue respectively. However, there were no significant differences in cAMP nor PKA expression between both types of tissues and in expression in any of the analyzed variables by recurrence status. The MOR and OGFR expression data from TCGA database were similar to our sample size data with lower expression of MOR and higher expression of OGFR in tumoural samples with a skewed distribution for MOR expression in tumor tissue both in patients with and without recurrence.

Conclusion

In patients with stage II and III colorectal cancer, overall expression of MOR and OGFR was significantly increased but was not different between previously matched patients with or without recurrence. No differences were found in the analyzed metabolic pathway of cAMP-PKA: These results were confirmed by an in silico analysis of samples from the TCGA-GTEx database.

Laser Capture Microdissection of Single Neurons with Morphological Visualization Using Fluorescent Proteins Fused to Transmembrane Proteins

Gene expression analysis in individual neuronal types helps in understanding brain function. Genetic methods expressing fluorescent proteins are widely used to label specific neuronal populations. However, because cell type specificity of genetic labeling is often limited, it is advantageous to combine genetic labeling with additional methods to select specific cell/neuronal types. Laser capture microdissection is one of such techniques with which one can select a specific cell/neuronal population based on morphological observation. However, a major issue is the disappearance of fluorescence signals during the tissue processing that is required for high-quality sample preparation. Here, we developed a simple, novel method in which fluorescence signals are preserved. We use genetic labeling with fluorescence proteins fused to transmembrane proteins, which shows highly stable fluorescence retention and allows for the selection of fluorescent neurons/cells based on morphology. Using this method in mice, we laser-captured neuronal somata and successfully isolated RNA. We determined that ∼100 cells are sufficient to obtain a sample required for downstream applications such as quantitative PCR. Capability to specifically microdissect targeted neurons was demonstrated by an ∼10-fold increase in mRNA for fluorescent proteins in visually identified neurons expressing the fluorescent proteins compared with neighboring cells not expressing it. We applied this method to validate virus-mediated single-cell knockout, which showed up to 92% reduction in knocked-out gene RNA compared with wild-type neurons. This method using fluorescent proteins fused to transmembrane proteins provides a new, simple solution to perform gene expression analysis in sparsely labeled neuronal/cellular populations, which is especially advantageous when genetic labeling has limited specificity.

Shape decomposition algorithms for laser capture microdissection

Background

In the context of biomarker discovery and molecular characterization of diseases, laser capture microdissection is a highly effective approach to extract disease-specific regions from complex, heterogeneous tissue samples. For the extraction to be successful, these regions have to satisfy certain constraints in size and shape and thus have to be decomposed into feasible fragments.

Results

We model this problem of constrained shape decomposition as the computation of optimal feasible decompositions of simple polygons. We use a skeleton-based approach and present an algorithmic framework that allows the implementation of various feasibility criteria as well as optimization goals. Motivated by our application, we consider different constraints and examine the resulting fragmentations. We evaluate our algorithm on lung tissue samples in comparison to a heuristic decomposition approach. Our method achieved a success rate of over 95% in the microdissection and tissue yield was increased by 10–30%.

Conclusion

We present a novel approach for constrained shape decomposition by demonstrating its advantages for the application in the microdissection of tissue samples. In comparison to the previous decomposition approach, the proposed method considerably increases the amount of successfully dissected tissue.

Transcriptomics and solid tumors: The next frontier in precision cancer medicine

Transcriptomics, which encompasses assessments of alternative splicing and alternative polyadenylation, identification of fusion transcripts, explorations of noncoding RNAs, transcript annotation, and discovery of novel transcripts, is a valuable tool for understanding cancer mechanisms and identifying biomarkers. Recent advances in high-throughput technologies have enabled large-scale gene expression profiling. Importantly, RNA expression profiling of tumor tissue has been successfully used to determine clinically actionable molecular alterations. The WINTHER precision medicine clinical trial was the first prospective trial in diverse solid malignancies that assessed both genomics and transcriptomics to match treatments to specific molecular alterations. The use of transcriptome analysis in WINTHER and other trials increased the number of targetable -omic changes compared to genomic profiling alone. Other applications of transcriptomics involve the evaluation of tumor and circulating noncoding RNAs as predictive and prognostic biomarkers, the improvement of risk stratification by the use of prognostic and predictive multigene assays, the identification of fusion transcripts that drive tumors, and an improved understanding of the impact of DNA changes as some genomic alterations are silenced at the RNA level. Finally, RNA sequencing and gene expression analysis have been incorporated into clinical trials to identify markers predicting response to immunotherapy. Many issues regarding the complexity of the analysis, its reproducibility and variability, and the interpretation of the results still need to be addressed. The integration of transcriptomics with genomics, proteomics, epigenetics, and tumor immune profiling will improve biomarker discovery and our understanding of disease mechanisms and, thereby, accelerate the implementation of precision oncology.