padpadpadpad / rTPC

R package to help fit Thermal Performance Curves
https://padpadpadpad.github.io/rTPC/
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Two additional models recommend for builting into rTPC. #54

Open Jinta0Li opened 11 months ago

Jinta0Li commented 11 months ago

Dear authors,

I really like your packages, and have used it to analysis my data.

I would like to recommend two models, which both are derived from transition state theory. Perhaps you could consider building them into your rTPC.

  1. The first one is the so-called MMRT (Macromolecular Rate Theory), which has recently been increasingly used in Ecology.

MMRT was firstly introduced by Hobbs et al. (2013). And Liang et al (2017) proved that the MMRT is formally equivalent to a second-order log-polynomial model (ie, ln y = a + b×T + c×T^2). More recently, it appears that a modified version of MMRT has been developed (Prentice et al, 2020; Alster et al, 2023). Refs: Hobbs, et al. Change in Heat Capacity for Enzyme Catalysis Determines Temperature Dependence of Enzyme Catalyzed Rates. ACS Chem. Biol. 2013, 8, 11, 2388–2393. https://doi.org/10.1021/cb4005029 Liang, et al. Macromolecular rate theory (MMRT) provides a thermodynamics rationale to underpin the convergent temperature response in plant leaf respiration. Glob Change Biol. 2018; 24: 1538–1547. https://doi.org/10.1111/gcb.13936 Prentice, et al. The Inflection Point Hypothesis: The Relationship between the Temperature Dependence of Enzyme-Catalyzed Reaction Rates and Microbial Growth Rates. Biochemistry 2020, 59, 38, 3562–3569. https://doi.org/10.1021/acs.biochem.0c00530 Alster, et al. Quantifying thermal adaptation of soil microbial respiration. Nat. Commun. 2023, 14, 5459. https://doi.org/10.1038/s41467-023-41096-x

  1. And the another is a very recent model introduced by Arroyo et al. (2022) in PNAS. Their model provides a good fit to empirical data for a wide variety of biological rates, times, and steady-state quantities, from molecular to ecological scales, and it takes a simple form ln⁡y=ln⁡y0 - bx - a ln⁡x. (x = T^-1) Refs: Arroyo, et al. A general theory for temperature dependence in biology. Proceedings of the National Academy of Sciences, 2022, 119(30): e2119872119. https://doi.org/10.1073/pnas.2119872119
padpadpadpad commented 11 months ago

Hi @Jinta0Li. Thanks for reaching out. Would you be willing to help add these models to the R package? If so I can advise on what information we would need.

Cheers Dan

Jinta0Li commented 11 months ago

Yes, I would very much like to. Please tell me what I need to do.

Cheers,

Jintao

padpadpadpad commented 11 months ago

Nice!

rTPC is basically a set of helper functions to fit the most common rTPC models, but the fitting process is done using nls.multstart and other packages. Consequently if you just wrote your own function, it would like work with the "fitting many models" routine, apart from you would have to set your own start values and lower and upper limits. I think calc_params() should also work out the box as it just uses the model object to calculate the extra traits.

Things we would need are:

Happy to help where needed.

We could track progress in here. Do you have a function for either of the models?

Jinta0Li commented 11 months ago

Got it. While I'm not a code expert, I will try my best to consolidate what I know about these models and maybe send you what you need next week (Currently, I am doing a field sampling).

padpadpadpad commented 2 weeks ago

How did you get on @Jinta0Li ?

Jinta0Li commented 2 weeks ago

Hi @padpadpadpad ,

Thanks for your patience! I’ve completed the three models we discussed. They work well with both the chlorella_tpc dataset from rTPC and my own dataset, fitting all curves successfully.

I’ve attached the .R files here for you to review:

If you need any additional files or specific information about the models, please feel free to let me know, and I’ll be happy to provide it.

Cheers, Jintao models_for_rTPC_Jintao.zip