Spencer, R. G. | bioRxiv Science

bioRxiv2026

Biotic versus environmental controls on microbial degradation of permafrost organic matter

Permafrost thaw exposes ancient organic matter to microbial degradation, which is predicted to release globally significant quantities of greenhouse gases into the atmosphere. Though microorganisms drive these processes, the relative importance of biotic (taxonomic and functional community composition) versus environmental (e.g., soil physicochemistry) drivers and their interactions are unknown. Using a novel in situ thaw experiment conducted at the Cold Regions Research and Engineering Laboratorys Permafrost Tunnel near Fairbanks, Alaska, we experimentally separated the effects of soil physicochemistry and microbial communities under "real-world" thaw conditions. To simulate thaw, active layer soil, Holocene permafrost (2 kya), and Pleistocene permafrost (40 kya) were sterilized, inoculated with microbial communities from the different soils, enclosed in 0.22 {micro}m membrane bags to prevent immigration, and buried in the active layer. We retrieved the bags after two weeks and two months of thaw and characterized microbial community structure (16S rRNA and ITS2 amplicon sequencing), functional potential (metagenome sequencing), and soil organic matter (OM) composition at the molecular level (FT-ICR MS). Soil had a stronger effect on bacterial community and gene assemblages than inoculum, and the effects of inoculum were stronger and longer-lasting on community structure than functional potential. Pleistocene permafrost initially contained approximately eleven times more dissolved organic carbon than the other soils, and was enriched in OM derived from microbial necromass and low molecular weight organic acids. This carbon was rapidly depleted during thaw and OM compositional characteristics became increasingly similar to active layer and Holocene permafrost, paralleling shifts in Pleistocene permafrost functional gene profiles and bacterial community structure towards those of other soils. Overall, this work provides new insights into the susceptibility of OM to microbial degradation in compositionally distinct permafrost soils, and ways in which Pleistocene Yedoma permafrost carbon is likely to be particularly vulnerable to permafrost thaw.

microbiology↗

bioRxiv2025

Myelin Mapping in the Human Brain Using an Empirical Extension of the Ridge Regression Theorem

PurposeMyelin water fraction (MWF) mapping in the central nervous system is a topic of intense research activity. One framework for this requires parameter estimation from a decaying biexponential signal. However, this is often an ill-posed nonlinear problem resulting in unreliable parameter estimates. For linear least-squares (LLS) problems, the ridge regression theorem (RRT) shows that a Tikhonov regularization parameter exists that will reduce mean square error (MSE) in parameter estimates. We present and apply a nonlinear version of the RRT,{lambda} -NL-RR, to MWF mapping. MethodsFor simulated and experimental data, we estimated parameter values with conventional nonlinear least-squares (NLLS) and compared these with values obtained from{lambda} -NL-RR, with the regularization parameter value defined by generalized cross validation. We applied regularization only to signals identified as biexponential according to the Bayesian information criterion. ResultsUnder conditions of modest SNR and closely spaced exponential time constants in which conventional biexponential analysis methods yield particularly inaccurate results,{lambda} -NL-RR decreases MSE by ~10-15%. ConclusionRegularization of the NLLS parameter estimation problem for the biexponential model decreased MSE for simulated and in vivo MRI brain data. In addition, this work provides a general framework for regularization of a broad class of NLLS problems.

biophysics↗