week-03-hw-lab-automation/_index.md
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Post lab questions
In this Review, the authors highlight the importance of single cell resolution analysis aided by robotic automated microfluidics.
The traditional method of bulk analysis averages signals across entire cell populations, maskin critical biological diversity at single cell levels. In a population of cells, there are different cell populations, due to genetic, epigenetic and environmental variations. In cancer and immunology research this is fundamental because even a small fraction of drug-resistant cells can drive disease progression and treatment failure. The process of screening diverse methods of treatment or looking for molecular markers could make a decisive impact on how we treat this diseases.
Microfluidics enable the single cell analysis at scale. By confining cells within microchambers or tiny droplets, microfluidics systems achieve a high throughput of isolated cells, that we cand study individually and discover new sub populations improving the treatment methods or researching the disease.
Another fundamental aspect that the paper mentions is the high reliability that robotic automation achieve. Removing human variability from the mos sensitive and repetitive steps is fundamental, avoiding the need for specialized personnel or chip-to-chip variation.
Here are some quotes from the paper that I found relevant to my final proyect.
“Ctortecka et al. developed an automated platform for multiplexed single-cell proteomics using a custom-designed microfabricated chip (proteoCHIP) coupled with the high-precision robotic system cellenONE”
“By eliminating manual handling and carrier proteome dependence, the platform enabled the identification of ∼2600 proteins across 170 single cells, with high reproducibility and over 90% data completeness per run.”
In this quote, the authors show how single cell analysis could be improved by robotic automation, enabling high reproducibility in proteomics assays that could improve the throughput of sreening at the single cell level different populations.
- Automation in my final project.
- Sample preparation before chip loading
- One of the most critical and error-prone steps is preparing the biological sample before it even reaches the microfluidic chip. Robotic liquid handlers could standardize and automate several of these upstream tasks.
- Cell counting and viability assessment could be performed robotically with a consistent technique, ensuring that only samples meeting predefined quality thresholds proceed to the chip.
- Reagent preparation — including buffers, lysis solutions, and barcoding reagents — could be dispensed with picoliter-to-nanoliter precision, eliminating the pipetting variability that a human operator inevitably introduces.
This matters enormously in cancer research because tumor samples from biopsies are often scarce and irreplaceable. A robot like the Opentrons OT-2, mentioned in the paper for cell migration assays, could handle these preparatory steps reliably within a sterile environment, reducing the risk of contamination and sample loss before the experiment even begins.
Droplet generation and handling The paper highlights the RAD microfluidics approach, where a commercial Tecan Freedom EVO robot was coupled to droplet microfluidic components including generators, mergers, and sorters, creating a fully automated droplet workflow. A similar integration in the chip could control the timing and flow rates of droplet generation with grater consistency than manual syringe pump operation. Improving the uniformity of single cell encapsulation and its efficiency.
Post-isolation sample handling for Omics workflows Once the cells are isolated, the preparation for different omics analysis is a process sensitive to errors. In the paper, the authors name a variety of examples (nanoPOTS or PiSPA) that uses robotic systems to perform nanoliter-scale cell lysis, enzymatic digestion and sample transfer with minimal loss, achieving a high rate of total proteins for proteomic analysis. Also for transcriptomic assays, some robots like proteoCHIP and cellenONE, could automate the coloading of barcoded beads of the isolated cells and perform the scRNA-seq by integrating different attachments.
Multiplexed screening of cancer subpopulations Other point of interest is the automation of screening processes. The robotics integration tool is perfect for this job, because they can run many experimental conditions in parallel without the increase of human effort. In the review, they mention the use of a OT-2 for the screening of 172 compunds across tens of thousends of cells.
Interactomics and functional assays For the interactomics and functional experiments, the robots could automate the timed adittion of stimuly, co culture partners or signalling molecules to the isolated cells in precise intervals
Generating data for AI-driven analysis
Most importantly, the robotic automation would allow the plataform to generate large and standarized datasets needed to train LLMs, that could be applied in every part of the process like cell clasification, data agumentation, multi omics integration and the interpetation of data.
Final project ideas
Microfluidic Lab-on-a-Chip System for Single-Cell Encapsulation in Tumor Heterogeneity Research
This project proposes the development of a droplet based microfluidic system lab-on-chip (LoC) platform designed for single cell encapsulation and isolation. The aim is to understand the intratumoral heterogeneity at the individual cell level. This approach help us to study cancer subpopulations. Coupled to diverse Omics studies could help us disentangle the dynamics of tumors.
The identification of rare tumor subpopulations (including drug-resistant and stem-like cells) is fundamental in cancer research and treatment options, because they drive disease progression and therapeutic failure. The conventional bulk analysis of tumor biopsies mask the failure of therapeutic drugs and the perseverance of important subpopulations that could . The single cell approach combined with the omics optic could give us a more complex understanding in the dynamics of the tumor development
A novel aptamer biosensor for the detection of herbicides in complex food matrices
This project proposes the development of an aptamer-based biosensor platform for the sensitive and selective detection of herbicide residues in complex food matrices.
In this project, we address a growing analytical challenge in food safety monitoring and regulatory compliance. Herbicide contamination in food products represents a critical public health concern as most widely used agrochemicals (e.g glyphosate) persist through food processing chains and remain undetected because of the analytical complexity of the matrices
The biosensing strategy is centered on the rational selection and optimization of DNA or RNA aptamers with a high binding affinity and specificity toward the target herbicide molecules. The choice for this molecule of recognition is based in the key advantages that aptamers offer over conventional antibodies, like grater chemical stability, lower production costs, easier functionalization and the capacity for in vitro selection wia systematic evolution of ligand by exponential enrichment (SELEX).
Viral vector-based Caspase delivery system for targeted apoptosis induction in solid tumors
This project proposes the design and development of a viral vector-based delivery platform engineered to selectively deliver and activate caspase proteins within solid tumor cells, exploiting the intrinsic machinery of programmed cell death to achieve targeted oncological treatment.
This delivery system addresses a fundamental limitation of conventional cancer therapies which lack tumor specificity,, inducing systemic toxicity and off target damage to healthy tissues while frequently failing to eradicate drug-resistant or apoptosis-evasive tumor subpopulation that drive recurrence and metastatic progression
Caspases are the executioner proteases of the apoptotic cascade. Tumor cells commonly evade apoptosis through the downregulation or mutation of pro-apoptotic signaling components. By directly delivering exogenous caspases (particularly effector caspases) into tumor cells via a viral vector this approach bypasses the upstream signalling failures that confer apoptotic resistance in tumor cells.