the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jan 2025
Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers
Abstract. Rivers receive substantial dissolved organic matter (DOM) input from the land and transport it to the ocean. As DOM travels through watersheds, it undergoes biotic and abiotic transformations that impact biogeochemical cycles and any subsequent CO2 release into the atmosphere. While recent research has increased our mechanistic knowledge of DOM composition within watersheds, DOM development across broad spatial distances and within divergent biomes is under investigated. Here, we combined DOM characterization, geochemical analyses, and shotgun metagenomics to analyze samples from seven rivers ranging from the U.S. Pacific Northwest to Berlin, Germany. Initial analyses revealed that many DOM properties were distinguished by river type (e.g., wastewater, headwater) and that geochemistry often explained variation across rivers. At a global scale, analyses rooted in meta-metabolome ecology indicated that DOM was structured overwhelmingly by deterministic selection. When controlling for scale, however, analyses indicated that ecological assembly dynamics were again partially structured by river type. Finally, microbial analyses revealed that many riverine microbes from our systems shared core metabolic functional potential while differing in peripheral capabilities in across the rivers. Further analysis of the carbon degradation potential for recovered metagenomically assembled genomes indicated that the sampled rivers had strong taxonomically conserved niche differentiation and that carbon degradation potential diversity was significantly related to organic matter diversity. Together, these results help us uncover interconnections between the development of DOM, riverine geochemistry, and microbial functional potential.
Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-3899', Anonymous Referee #1, 08 Apr 2025
The manuscript is well written, and the data analysis is very thorough and state of the art. The authors attempted to connect geochemical characteristics, DOM molecule formulas, and metagenomics based on 7 rivers across a large spatial scale. They basically concluded that DOM properties can be distinguished by river type and geochemistry of the rivers differed. They also showed that the microbes of the rivers shared core functional potential. While I appreciate the data and particularly the excellent data analysis, I feel that the conclusions are not that novel and I also have some concerns that the authors need to address.
The several rivers seemed to be randomly selected without any justification. It needs to be clearly stated why these rivers are selected and how representative they are in terms of the world’s rivers. It is also stated the river types, wastewater vs headwater, but more concrete data or logic connections are needed. What are the nutrient data? Other than the RDA in Figure 2, there is no nutrient data reported in the manuscript. Also, how exactly can you connect DOM to the wastewater, directly input of DOM or through nutrient-inspired algal blooms? In general, statistical analysis is fancy but there is little or no mechanistical connection. I feel that this shortcoming is throughout the manuscript, such as the connection between DOM and metagenomics.
A set of geochemical parameters were selected for the work, including Cl, Mg, TN F, Fe etc., but why? For example, why not Chla and why not dissolved oxygen? Chla would be very straightforward to connect to DOM and microbes. I am not saying you have to include Chla, but need to justify why you chose this specific set of parameters among the numerous choices.
The authors used metabolome for the DOM characterization. I am not very sure this is an accurate definition as it is assumed all the formulas obtained from FTICR-MS are metabolites. I don’t think this is true because there could be contribution from abiotic reactions or selective preservation.
FTICR-MS is a non-quantitative technique; thus, it is great that the authors chose to use ‘presence or absence” to process the data. But this is still tricky if you don’t inject the same amount of carbon (or DOC) in samples when you are trying to compare them. In other words, the absence or presence of a specific molecule may depend on the matrix or DOC concentration. Some QA/QC on this aspect needs to be added.
Citation: https://doi.org/10.5194/egusphere-2024-3899-RC1 -
RC2: 'Comment on egusphere-2024-3899', Anonymous Referee #2, 23 Apr 2025
In this study, the authors sampled several rivers primarily distributed in the U.S.A, with one additional river in Germany and another one in Israel. They generated an extensive dataset including DOM molecular composition, metagenome assembled genome, inorganic ions, and organic carbon concentration. Whereas the dataset and the data themselves are of high quality, the study is not adding any novelty compared to the literature. Moreover, this study is not a global study. It is mostly a study of rivers in the U.S.A. and therefore, I am not convinced by the global aspect. I think the authors have to carefully rethink their study as I personally do not recommend publication in its current form but believe it can become a nice manuscript.
Please work a bit more on the abstract. It contains quite a lot of jargon and is not down to the point.
The introduction is not down to the point and does not introduce the topic well enough. The second and third paragraphs are just a list of studies, mostly from the authors themselves, without any link or any rationale behind it. They just tell us that people have studied microbes and DOM in rivers before. After reading the introduction, I was not convinced that this study was needed, nor that a meta-metabolome ecology was needed. The introduction forces us to question the choice made by the authors instead of helping us understand the study. For instance, why the author did not use a network analysis like previously done (Zhou et al, 2024)? A network approach is best suited “to characterize the microbes that interact with and alter river corridor DOM” “and to observe connections between DOM and the microbes that consume it”. Why the author did not use more traditional multivariate analysis as typically done (e.g. Ezzat et al, 2025)? Most of their results are derived from multivariate analysis anyway. So the meta-metabolome was not needed here. Why the authors used ultra-high resolution mass spectrometry when other measurements suffice (e.g. Kohler et al 2024)? I recommend the authors to drastically revise their introduction to ensure the goal, relevance, and novelty of the study are all clear. Similarly, I would recommend the authors avoid over-citing themselves. Currently more than a quarter of the references are from the authors themselves, this is not normal, even if the authors want to claim they are leader in their fields.
In the methods section, I am puzzled by the reasoning of the author to convert the FT-ICR-MS data to presence/absence only whereas they consider the abundance of MAGs. The same limitation exists with FT-ICR-MS data than with metagenome data. It is not logical to convert one dataset into presence/absence only and not the other one. This is particularly concerning because it is unclear whether the results would remain the same if the author used richness instead of Shannon for the genomic data or if the author used Shannon instead of richness for the FT-ICR-MS data.
In the Results and Discussion section, it is disturbing that the results are not presented using the past tense. It gives the impression that a specific result is a general truth. Furthermore, much like in the introduction, the authors focus mostly on their previous work. Consequently, it feels like there is nothing novel. Except for some river parameters, I fail to see novelty in those results or their interpretation. The Results and Discussion section need more discussion. I am pretty sure this study can advance our knowledge of riverine microbes and their interaction with DOM, but it is up to the authors to tell us how it does it.
Minor comment and typos:
There were many typos and grammatical mistake in the text. I only reported those that obviously stood out, down to the beginning of the Results and Discussion section.
Line 38: Why Berlin, Germany and not Israel or Middle East? On the map, the westernmost rivers are in Oregon/Washington, and the easternmost river is the Jordan river in Israel. Having Berlin here is a bit odd.
Line 39: Define geochemistry. Too much jargon for an abstract.
Line 41: Which scale?
Line 44: in across the rivers --> across the rivers
Line 45: for recovered metagenomically assembled genomes --> from recovered metagenomically assembled genomes
Line 92: reveal --> revealed
Line 116-117: What do you mean by “and shotgun metagenomic sequencing partnered to ecological analyses”. Please specify what ecological analyses and how they partnered with the metagenome data.
Line 127: the seven rivers --> seven rivers
Line 158: What was the volume of surface water collected?
Line 159: In total, 690 total samples. Remove one “total”.
Line 167-169: No clogging of the filter at any site? Even with Sterivex filters, clogging does occur. Please specify if less water was passed through the filters at some sites and what was done if clogging occurred. Specifically, how the replicates were handled.
Line 170-171: Please provide reference of the probe use for temperature, pH, etc.
Line 171-172: Please specify the vials were pre-combusted before injecting the DOM samples.
Line 198: Reference of the PPL cartridges? And what does PPL stand for?
Line 209: “or had an isotopic signature” does that mean authors removed all peaks that contained a e.g. 13C? It is quite unclear as written here.
Line 274: on the NovaSEQ6000 platform on a S4 flow cell --> on a NovaSEQ6000 platform using a S4 flow cell
Line 302: and using --> using
Line 351: It is unclear what is meant by “we see that each river has characteristic geochemical parameter values”. Please develop further and define what “characteristic geochemical parameter values” mean.
Line 363-364: Examining carbon data for combined pore and surface water samples à Examining carbon data from combined pore and surface water samples
Line 624: A network is better suited to identify those relationship than the speculation proposed by the authors.
References:
Zhou L, Wu Y, Zhou Y, Zhang Y, Xu H, Jang KS, Dolfing J, Spencer RG, Jeppesen E. Terrestrial dissolved organic matter inputs drive the temporal dynamics of riverine bacterial ecological networks and assembly processes. Water Research. 2024 Feb 1;249:120955.
Ezzat L, Peter H, Bourquin M, Busi SB, Michoud G, Fodelianakis S, Kohler TJ, Lamy T, Geers A, Pramateftaki P, Baier F. Diversity and biogeography of the bacterial microbiome in glacier-fed streams. Nature. 2025 Jan 1:1-9.
Kohler TJ, Bourquin M, Peter H, Yvon-Durocher G, Sinsabaugh RL, Deluigi N, Styllas M, Vanishing Glaciers Field Team Styllas Michael 1 Schön Martina 1 Tolosano Matteo 1 de Staercke Vincent 1, Battin TJ. Global emergent responses of stream microbial metabolism to glacier shrinkage. Nature Geoscience. 2024 Apr;17(4):309-15.
Citation: https://doi.org/10.5194/egusphere-2024-3899-RC2
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