COBRAxy: spatial and single-cell metabolic modelling

[kiaradamiani]

Background

Galaxy is an open-source platform designed to make advanced bioinformatics analyses accessible and reproducible. Among its many applications, constraint-based metabolic modeling (CBM) plays a pivotal role in exploring cellular metabolism through predictive simulations of flux distributions in metabolic networks.

Current tools in the Galaxy ecosystem, such as MaREA4Galaxy, provide robust capabilities for analyzing metabolic networks based on gene expression data. However, these tools are primarily focused on bulk RNA-seq data and do not yet fully support single-cell RNA-seq (scRNA-seq) or spatial transcriptomics data. High-resolution single-cell and spatial data offer unprecedented opportunities to study metabolic heterogeneity and spatially localized metabolic activities but require significant adaptations to workflows and computational tools.

Existing Python libraries, such as COBRApy, implement key CBM techniques, including flux balance analysis (FBA) and flux variability analysis (FVA). Efforts like cobraxy have already ported some of these functionalities into Galaxy, but gaps remain—particularly in the support for single-cell FBA (scFBA) and the integration of spatial transcriptomics workflows. Moreover, there is a need to improve the computational efficiency of sampling algorithms by interfacing directly with solvers such as Gurobi o Glpk.

This project aims to address these gaps by extending Galaxy’s CBM capabilities to support single-cell and spatial data integration, along with optimizations to statistical testing and computational efficiency.

Goal

This project builds on the foundation of MaREA4Galaxy, a Galaxy tool designed for metabolic reaction enrichment analysis, expanding its scope to:

1. Support single-cell metabolic analysis: Implement models like scFBA, which integrate transcriptomics data into population-based flux models to capture metabolic heterogeneity at single-cell resolution.
2. Integrate spatial transcriptomics workflows: Enable mapping of metabolic activities onto physical tissue architectures and co-localization analyses.
3. Improve computational efficiency: Optimize the sampling algorithm by directly interfacing with solvers like Gurobi or Glpk, bypassing intermediate steps in COBRApy to reduce runtime.
4. Enhance statistical testing: Introduce advanced methods for pathway enrichment analyses, including p-value adjustments (e.g., Bonferroni, FDR) and Bayesian approaches to improve result reliability.
5. Develop visualization tools: Enable spatial overlays and interactive visualizations for flux distributions and pathway activities.

Difficulty Level: Medium

This project is categorized as medium difficulty because the integration of existing Python tools into Galaxy workflows is straightforward but requires careful adaptation to handle single-cell and spatial data effectively.

Size and Length of Project

• medium: 175 hours
• 12 weeks

Note that the project length for small projects should be 10-12 weeks.

Skills

Essential skills:

• Python programming
• Constraint-based metabolic modeling (e.g., FBA, scFBA)

Nice to have skills:

• Galaxy tool development
• Experience with single-cell scRNA-seq

Public Repository

The existing COBRAxy tools can be found in the following repository:
COBRAxy on Galaxy ToolShed

Potential Mentors

Chiara Damiani, chiara.damiani@unimib.it
Bruno Galuzzi , brunogiovanni.galuzzi@cnr.it

Getting started:

• have a look at the demo of current COBRAxy version here: http://marea4galaxy.cloud.ba.infn.it/galaxy
• read the references listed in the readme of each tool of the toolsuite
• try perform an analysis using this tutorial: https://drive.google.com/file/d/125l1SqjJ2wrnQl9e7D6_UdxqmK9afsbI/view?usp=sharing
• read the preprint on spatial flux balance analysis for flux visualization ideas: https://www.biorxiv.org/content/10.1101/2024.11.28.625842v2

[kriishukla]

Hi Chiara and Bruno,

I’m Krishna, with experience in Python programming and constraint-based metabolic modeling (FBA, scFBA). I’m interested in contributing to the project aimed at extending Galaxy's CBM capabilities for single-cell and spatial data integration. I would love to help with integrating single-cell metabolic analysis, optimizing computational efficiency, and developing visualization tools.

Could we set up a brief meeting or channel to discuss the project scope and how I can best contribute? I’d also be happy to share my relevant experience and past work.

Best regards,
Krishna

[kiaradamiani]

Dear Krishna,

Thank you for your interest in the project.

We can plan a call. Would Monday at 4:00 PM (CET) work for you? Please let me know if that time suits you or if you prefer another slot.

Looking forward to your response,
Chiara

[kriishukla]

Sure, this works for me.

…

On Mon, Feb 10, 2025, 3:49 PM kiaradamiani ***@***.***> wrote: Dear Krishna, Thank you for your interest in the project. We can plan a call. Would Monday at 4:00 PM (CET) work for you? Please let me know if that time suits you or if you prefer another slot. Looking forward to your response, Chiara — Reply to this email directly, view it on GitHub <#248 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A46C2YGDGJIDDD6NKTPZZE32PB4MJAVCNFSM6AAAAABVVIKOO2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDMNBXGU2DKMZSGY> . You are receiving this because you commented.Message ID: ***@***.***>

[kriishukla]

Are we going to reschedule? I didn't get any invite from you.

[kiaradamiani]

I am sorry Krisna, I meant next Monday (March 17th). I am sorry for the misunderstanding.
Is it ok next week for you?

[kriishukla]

Yes, it works for me.

…

On Mon, Feb 10, 2025, 9:08 PM kiaradamiani ***@***.***> wrote: I am sorry Krisna, I meant next Monday (March 17th). I am sorry for the misunderstanding. Is it ok next week for you? — Reply to this email directly, view it on GitHub <#248 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/A46C2YGQBGSYB73YDFHOJJT2PDBVPAVCNFSM6AAAAABVVIKOO2VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDMNBYGQZDONRRGQ> . You are receiving this because you commented.Message ID: ***@***.***>

[khanspers]

NRNB has been accepted as a mentoring organization for GSoC 2025. The contributor application period is March 24 – April 8. Here are some useful links:

GSoC contributor guide
NRNB project proposal template
Eligibility requirements
Full program timeline

[roshni-b]

Hi Chiara, Hi Bruno,

I am Roshni, a computational biology PhD student, currently working on phylogenetic modeling for single-cell transcriptomics data, and am familiar with spatial workflows. I'd love to contribute to this project. Could we set up a meeting to discuss the project scope for GSoC 2025?

Best,
Roshni

[doramarcec]

Dear Chiara and Bruno,

I am Dora, a Master's student in Bioinformatics and Systems Biology. I am currently working on my research project, which aims to build an interactome model from single-cell and spatial transcriptomics data. Throughout my degree, I've gained proficiency in Python programming and experience in constraint-based metabolic modelling (specifically, FBA, using a COBRApy package) and I'm eager to contribute to this project. Would you be available for a brief meeting sometime next week or the week commencing on March 10th to discuss the project in more detail?

Best wishes,
Dora

[brunoG89]

Dear participants,

Thank you for your interest in our project. To have the opportunity to discuss it with all of you, we are planning a web meeting on Wednesday at 2 p.m. UTC+1. The link to the event is:

https://unimib.webex.com/meet/chiara.damiani

Please RSVP.

Best regards,
Chiara and Bruno