Metabolites Submission Guide: MDPI Process (2026)

Metabolites is not a stronger version of a subscription metabolomics journal, and it is not a weaker one. It is a different model. MDPI built it around speed and soundness-based review: the editorial question is whether the analytical work is sound, reproducible, and within scope, not whether it ranks among the most novel metabolomics findings of the year. That model shapes everything about how you should prepare the package.

Two consequences matter most. First, the journal is section-based and organized by metabolomics subfield (Endocrinology and Clinical Metabolic Research, Microbiology and Ecological Metabolomics, Plant Metabolism, and others), so scope fit is assessed against a specific section rather than a vague "is this interesting" bar. Second, the pre-check is fast and reporting-driven, so analytical completeness is rewarded and incompleteness is punished early.

A biologically interesting manuscript with no metabolite-identification levels and no deposited raw data can be returned before a reviewer ever sees it, while a competent, complete, in-scope study moves quickly.

The unusual upside: because Metabolites is soundness-based, a careful method paper, a well-controlled negative or null metabolomics result, or a rigorous validation study has a real home here. Subscription metabolomics titles that select on novelty routinely turn those away. If your contribution is analytical rigor rather than a headline biomarker, this is a venue where rigor is the product.

The core fit for most submissions is the original research article. It works best when the metabolomics question is central, the analytical pipeline is reproducible from the text and supplement, and the identification, deposition, and QC reporting are complete on first upload.

Ask these questions before you submit:

• is the metabolite or metabolism question the actual subject of the paper, or is it a downstream readout of a genomics or proteomics study?
• can a reader reproduce the acquisition, processing, and identification pipeline from the manuscript and supplementary files alone?
• does every reported metabolite carry a confidence level, and is the raw data deposited with an accession?
• are the QC samples, blanks, and batch-correction steps described, or are they assumed?

If the answers are uncertain, the analytical-reporting problem is usually more important than the biology problem.

The pre-check editor is answering a short list of questions fast.

On scope, the editor asks whether the manuscript belongs in a metabolism or metabolomics journal and in which section. If the metabolite relevance is thin or bolted on, the paper is redirected or returned. On soundness, the question is whether the analytical methods are reproducible and the identifications defensible. Metabolites does not require the finding to be field-defining, but it does require the metabolomics to be done correctly and reported in full, down to the identification level for each compound.

On reporting integrity, the editor checks whether raw-data deposition, metabolite-identification levels, and quality-control documentation are present. MDPI runs integrity and plagiarism checks at pre-check, and a metabolomics paper with no MetaboLights or Metabolomics Workbench accession and no QC samples reads as not ready, regardless of how the biology is framed. On completeness, the editor looks for the declarations block. A manuscript missing Author Contributions, Funding, Ethics, or Data Availability statements reads as not ready even when the analytics are fine.

Manuscript structure: Metabolites expects a defined section set: Abstract, Keywords, Introduction, Materials and Methods, Results, Discussion, Conclusions, plus the declarations block. Original research and systematic reviews use a structured abstract of around 200 words. The Materials and Methods is the section the pre-check editor and reviewers weight most heavily for a metabolomics paper, because that is where acquisition, processing, identification, and QC live. The metabolite-identification level and the deposition accession should both be visible there and in the Data Availability Statement, not buried in a supplementary note.

Analytical reporting readiness: Provide full instrument and pipeline detail so the metabolomics can be reproduced: platform (LC-MS, GC-MS, NMR, CE-MS), column and gradient or pulse sequence, acquisition parameters, software and versions for peak picking and alignment, the identification approach, and the confidence level assigned to each reported metabolite under the MSI scale. A study that names metabolites without stating how confidently each was identified is the most common reviewer-stage friction point.

Data deposition and quality control: Deposit raw and processed data to MetaboLights or Metabolomics Workbench and put the accession in the Data Availability Statement before you upload. Document the analytical QC explicitly: pooled QC samples run through the batch, blanks, internal standards, the metrics used to judge run quality, and any drift correction. These are not optional polish at a soundness-based journal; they are how reviewers decide whether the measurements can be trusted at all.

Declarations and ethics: Draft the Institutional Review Board or ethics statement (for human, animal, or clinical-cohort work), Informed Consent statement, Author Contributions (by initials), Funding, Data Availability, and Conflicts of Interest sections before you upload. At MDPI these are pre-check gates, not post-acceptance paperwork.

Figures, supplementary, and abstract assets: A graphical abstract is optional but common. For a metabolomics paper, supplementary material is where the heavy reporting lives: the full metabolite table with identification levels, m/z and retention-time or chemical-shift evidence, MS/MS spectra or NMR assignments, the QC results, and any pathway-enrichment outputs. Supply figures at high resolution, keep the main narrative focused, and use the supplement for the evidence a reviewer needs to verify each identification.

In our pre-submission review work with Metabolites manuscripts, five failure patterns generate the most consistent pre-check returns and reviewer friction, and each is testable against your own manuscript before you upload.

Across our metabolomics pre-submission reviews, the pattern that surprises authors most is that the Metabolites screen is not a novelty filter; it is an analytical-completeness-and-fit filter. The manuscripts that get returned fastest are rarely uninteresting. They are studies whose metabolite-identification reporting, raw-data deposition, or quality-control documentation is not ready for a fast, reporting-driven screen.

Manuscripts coming through pre-submission review for Metabolites split cleanly along five lines: no MSI identification levels on the reported metabolites; no deposited raw data behind a stub Data Availability Statement; no quality-control samples documented in the methods; biomarker claims with no validation cohort; and under-powered designs or clinical scope drift that outruns the analytics.

Metabolite identifications reported with no MSI confidence level

Pattern: a metabolite table with names and abundances but no confidence column. The single most common pattern we see is a results table that names dozens of metabolites with no confidence level attached to any of them. A reviewer cannot tell which were confirmed against an authentic standard (MSI Level 1), which are putative annotations from a spectral library (Level 2), which are only class-level (Level 3), and which are unknowns (Level 4).

At a soundness-based journal this is fatal, because the entire claim rests on whether the measurements mean what the authors say they mean. The testable version: open your main metabolite table and check that every row carries an explicit identification level and the evidence behind it (exact mass, MS/MS match, retention-time match to standard, or NMR assignment).

If the table is a list of names with abundances and nothing else, the reporting is not ready, and the fix is to add an identification-level column and the supporting evidence before you submit.

Check whether your Metabolites identifications carry defensible confidence levels →

Raw MS or NMR data not deposited, with a stub Data Availability Statement

Pattern: no MetaboLights or Metabolomics Workbench accession in the Data Availability Statement. The second pattern is a Data Availability Statement that reads only "data available on request," with no MetaboLights or Metabolomics Workbench accession. Metabolomics is a field with mature, expected repositories, and MDPI's pre-check treats deposition as a reporting gate.

We repeatedly see metabolomics studies where the processed feature table is in a supplementary spreadsheet but the raw spectra were never uploaded anywhere, which means no reviewer can re-process the data or check the identifications independently. The testable version: confirm you have a real accession from MetaboLights or Metabolomics Workbench, that it is named in the Data Availability Statement, and that what you deposited includes the raw acquisition files, not only a derived table.

If your statement points to "the corresponding author," the deposition is not ready.

Check whether your Metabolites data-deposition plan is complete for pre-check →

Missing analytical quality-control samples and batch documentation

Pattern: a methods section with no pooled QC, blanks, or drift correction. The third pattern shows up at the reviewer stage: a methods section that describes the biology and the instrument but never mentions quality control. No pooled QC samples interleaved through the run, no blanks, no internal standards, no statement of how run quality or signal drift was monitored.

For untargeted metabolomics in particular, reviewers read the absence of QC as evidence that batch effects and drift were never controlled, so any group difference could be analytical rather than biological. The testable version: walk your Materials and Methods and confirm it names the QC samples used, the blanks, the internal standards, the acceptance metrics for the run, and any drift or batch correction applied.

If a reviewer cannot tell whether your fold changes survived QC filtering, the analytics are not ready, and this is the highest-leverage fix before submission.

Check whether your Metabolites methods document analytical quality control →

"Biomarker" claims with no validation cohort

The fourth pattern is a discovery-only study that uses the word biomarker. A panel of metabolites separates cases from controls in a single, often small, discovery cohort, and the paper frames the result as a biomarker without any independent validation set, without cross-validation that guards against overfitting, and without reporting how the model behaves out of sample. Reviewers in the clinical-metabolic section are sharp on this.

The testable version: if your manuscript claims a biomarker or a diagnostic signature, confirm there is a validation cohort or, at minimum, a rigorous internal cross-validation with the performance reported honestly, and that the language matches the evidence. If you have one cohort and one model fit, call it a candidate or an association, not a biomarker.

Check whether your Metabolites biomarker claims match your validation evidence →

Under-powered designs and scope drift to clinical without analytics rigor

The fifth pattern pairs two related problems. The first is a study with too few biological replicates per group for the statistical claims it makes, where the metabolomics is treated as exploratory but the conclusions read as definitive. The second is scope drift: a clinical-cohort paper aimed at the clinical-metabolic section whose clinical framing outruns its analytical rigor, with patient narrative in the foreground and the metabolomics methods thin behind it.

Metabolites is section-based, and the clinical-metabolic editors expect the analytics to carry the same weight as the cohort. The testable version: confirm your sample size supports the statistics you report, that the statistical methods are named and appropriate for the design, and that the metabolomics methods are as detailed as the clinical description. If the clinical story could stand alone without the metabolomics, you are aimed at the wrong journal.

Each of these is something you can check against your own draft before you commit the submission. This guide tells you what Metabolites editors look for; the review tells you whether YOUR paper passes the pre-check before you upload.

Across the 60 manuscripts we have reviewed in Manusights pre-submission work for metabolomics and metabolic-biochemistry journals, including papers targeting Metabolites and its open-access peers, the identification-level gap and the missing-QC gap are the two patterns we flag most often. Paid Manusights reviews include a 60-day money-back guarantee, and we do not train models on submitted manuscripts. Run a [Metabolites submission package check](/ai-review?

target_journal=Metabolites&source_blog=metabolites-submission-guide&primary_concern=submission_readiness) to see whether your identification levels, deposition plan, and QC reporting will clear the MDPI pre-check.

Metabolites reports a median first decision near 16.7 days and a median submission-to-publication time of roughly 6 weeks. Treat these as planning ranges, not promises: clinical-cohort and large multi-omics manuscripts often run longer because reviewer search takes time in specialized subfields.

• Day 0: Submission via SuSy. The portal accepts the package and routes it to the section editor for pre-check.

• Days 1 to 3: Editorial pre-check. The editor screens scope fit, metabolomics reporting completeness (identification levels, deposition, QC), ethics, integrity, and plagiarism.

The fastest returns happen here, before any reviewer is invited.

• Days 3 to 7: Reviewer invitation. Manuscripts that pass pre-check enter single-blind reviewer search, typically targeting two or more reviewers in the relevant metabolomics subfield.

• Days 7 to 17: Peer review and first decision. Reviewer reports return and the editor issues the first decision, with a median near 16.7 days from submission.

Major revision is the most common outcome for papers that clear pre-check.

• Days 17 to 35: Revision and acceptance. Revisions are usually requested on a short clock; resubmission and a second review cycle commonly land acceptance inside a few weeks for in-scope, complete packages.

• Days 35 to 42: Production and publication. Median submission-to-publication runs near 6 weeks, so the slow part of the calendar is reviewer search and revision, not production.

What actually slows a Metabolites decision down

The 16.7-day median hides real variance, and the things that delay your specific paper are predictable. Reviewer search is slowest for narrow analytical subfields: a CE-MS plant-metabolomics paper has a smaller reviewer pool than a clinical LC-MS study, so it waits longer. Revisions stretch when reviewers ask for re-analysis that depends on data you did not deposit, because you then have to deposit, re-run, and re-document mid-revision instead of pointing to an existing accession.

And clinical-cohort papers in the clinical-metabolic section run longer when the statistics need rework, since the editor often routes a revised statistics section back to the same reviewer. None of these is avoidable by writing faster; all of them are avoidable by having identification levels, deposition, and QC complete on first upload.

This guide was researched and built from primary sources: the sources we checked include the Metabolites Instructions for Authors, the journal's aims-and-scope and journal-statistics pages, MDPI's research and publication ethics policy, the Metabolomics Standards Initiative reporting recommendations, and the deposition guidance from MetaboLights and Metabolomics Workbench, alongside Manusights pre-submission review patterns from metabolomics manuscripts deciding between Metabolites and peer journals. We compared current MDPI author guidance with recent Manusights work reviews from authors weighing Metabolites, Metabolomics (Springer), Journal of Proteome Research, Frontiers in Molecular Biosciences, and Scientific Reports. Last reviewed by the Manusights molecular and metabolic editorial team on 2026-06-07.

Source limitations: MDPI can update APC, article-format details, abstract caps, and editorial-process numbers after this review date, so verify final administrative details against the official Metabolites author pages before upload. Median timelines are reported by the journal and vary by subfield. Repository names and identification-level conventions evolve, so confirm current MetaboLights, Metabolomics Workbench, and MSI guidance before you deposit. Use this guide for the decision the official instructions cannot answer: whether your identification reporting, data deposition, and QC documentation are ready for the MDPI pre-check.

• Metabolites journal profile
• Best metabolomics journals
• Cell Metabolism submission guide
• Nature Metabolism submission guide
• International Journal of Molecular Sciences submission guide

Before you upload, run your manuscript through a Metabolites submission readiness check to catch the identification-level, deposition, and QC gaps the MDPI pre-check filters for. The check is free to run (/ai-review) and takes a single upload.