Taxonomic distribution of metabolic functions in bacteria associated with Trichodesmium consortia.

IMPORTANCE: Colonies of the cyanobacteria Trichodesmium act as a biological hotspot for the usage and recycling of key resources such as C, N, P, and Fe within an otherwise oligotrophic environment. While Trichodesmium colonies are known to interact and support a unique community of algae and particle-associated microbes, our understanding of the taxa that populate these colonies and the gene functions they encode is still limited. Characterizing the taxa and adaptive strategies that influence consortium physiology and its concomitant biogeochemistry is critical in a future ocean predicted to have increasingly resource-depleted regions.

Influence of soil depth, irrigation, and plant genotype on the soil microbiome, metaphenome, and carbon chemistry.

IMPORTANCE: Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions.

Ultra-sensitive isotope probing to quantify activity and substrate assimilation in microbiomes.

BACKGROUND: Stable isotope probing (SIP) approaches are a critical tool in microbiome research to determine associations between species and substrates, as well as the activity of species. The application of these approaches ranges from studying microbial communities important for global biogeochemical cycling to host-microbiota interactions in the intestinal tract. Current SIP approaches, such as DNA-SIP or nanoSIMS allow to analyze incorporation of stable isotopes with high coverage of taxa in a community and at the single cell level, respectively, however they are limited in terms of sensitivity, resolution or throughput. RESULTS: Here, we present an ultra-sensitive, high-throughput protein-based stable isotope probing approach (Protein-SIP), which cuts cost for labeled substrates by 50-99% as compared to other SIP and Protein-SIP approaches and thus enables isotope labeling experiments on much larger scales and with higher replication. The approach allows for the determination of isotope incorporation into microbiome members with species level resolution using standard metaproteomics liquid chromatography-tandem mass spectrometry (LC-MS/MS) measurements. At the core of the approach are new algorithms to analyze the data, which have been implemented in an open-source software ( https://sourceforge.net/projects/calis-p/ ). We demonstrate sensitivity, precision and accuracy using bacterial cultures and mock communities with different labeling schemes. Furthermore, we benchmark our approach against two existing Protein-SIP approaches and show that in the low labeling range used our approach is the most sensitive and accurate. Finally, we measure translational activity using 18O heavy water labeling in a 63-species community derived from human fecal samples grown on media simulating two different diets. Activity could be quantified on average for 27 species per sample, with 9 species showing significantly higher activity on a high protein diet, as compared to a high fiber diet. Surprisingly, among the species with increased activity on high protein were several Bacteroides species known as fiber consumers. Apparently, protein supply is a critical consideration when assessing growth of intestinal microbes on fiber, including fiber-based prebiotics. CONCLUSIONS: We demonstrate that our Protein-SIP approach allows for the ultra-sensitive (0.01 to 10% label) detection of stable isotopes of elements found in proteins, using standard metaproteomics data.

The Sugar Metabolic Model of Aspergillus niger Can Only Be Reliably Transferred to Fungi of Its Phylum.

Fungi play a critical role in the global carbon cycle by degrading plant polysaccharides to small sugars and metabolizing them as carbon and energy sources. We mapped the well-established sugar metabolic network of Aspergillus niger to five taxonomically distant species (Aspergillus nidulans, Penicillium subrubescens, Trichoderma reesei, Phanerochaete chrysosporium and Dichomitus squalens) using an orthology-based approach. The diversity of sugar metabolism correlates well with the taxonomic distance of the fungi. The pathways are highly conserved between the three studied Eurotiomycetes (A. niger, A. nidulans, P. subrubescens). A higher level of diversity was observed between the T. reesei and A. niger, and even more so for the two Basidiomycetes. These results were confirmed by integrative analysis of transcriptome, proteome and metabolome, as well as growth profiles of the fungi growing on the corresponding sugars. In conclusion, the establishment of sugar pathway models in different fungi revealed the diversity of fungal sugar conversion and provided a valuable resource for the community, which would facilitate rational metabolic engineering of these fungi as microbial cell factories.

Implications of sample treatment on characterization of riverine dissolved organic matter.

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (-), non-SPE (-), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (-) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for heterotrophic microbial respiration. Thus, we infer that the SPE (-) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (-) and SPE (+) to adequately characterize these molecules.

Chemical characterization of dissolved organic matter as disinfection byproduct precursors by UV/fluorescence and ESI FT-ICR MS after smoldering combustion of leaf needles and woody trunks of pine (Pinus jeffreyi).

Forested land plays an essential role in water supply across the United States (US). Smoldering commonly existing in wildfires contributes significantly to biomass consumption and gas emission, but its influence on source water quality has been rarely studied. Here, we investigated the impact of smoldering temperature (i.e., no burn, 250, 400, and 600 °C) on the nutrients, elements, and dissolved organic matter (DOM) of water extracts from the residues of the leaf needles and woody trunks of pine (Pinus jeffreyi) under the lab-simulated smoldering fire. Results showed the increase of pH and the yields of the dominated exchangeable cations of K+ and Mg2+, P, PO43--P, and SO42- with increasing temperature increasing from 250 to 600 °C, whereas significant decreases in the fraction of dissolved organic C in residue C with increasing temperature and the yields of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) after burnings. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) presented consistent results with UV/fluorescence, suggesting that the unburned materials contained more biodegradable tyrosine/tryptophan/soluble microbial byproduct-like compounds with high molecular weight (MW), whereas the 600 °C-smoldering materials composed of more aromatic, humified, fulvic/humic acid-like, and oxidized compounds with a potentially high density of C=C bonds had less reactivity in forming trihalomethanes (THMs) and haloacetonitriles (HANs). Our study indicates the smoldering-dominated prescribed fire as a potential forest management strategy for reducing biomass fuel and disinfection byproducts (DBPs) precursors in source water from forested lands.

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties.

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed 'meta-metabolome ecology.' Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as 'thermodynamic redundancy,' which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable concepts, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Re-routing of Sugar Catabolism Provides a Better Insight Into Fungal Flexibility in Using Plant Biomass-Derived Monomers as Substrates.

The filamentous ascomycete Aspergillus niger has received increasing interest as a cell factory, being able to efficiently degrade plant cell wall polysaccharides as well as having an extensive metabolism to convert the released monosaccharides into value added compounds. The pentoses D-xylose and L-arabinose are the most abundant monosaccharides in plant biomass after the hexose D-glucose, being major constituents of xylan, pectin and xyloglucan. In this study, the influence of selected pentose catabolic pathway (PCP) deletion strains on growth on plant biomass and re-routing of sugar catabolism was addressed to gain a better understanding of the flexibility of this fungus in using plant biomass-derived monomers. The transcriptome, metabolome and proteome response of three PCP mutant strains, ΔlarAΔxyrAΔxyrB, ΔladAΔxdhAΔsdhA and ΔxkiA, grown on wheat bran (WB) and sugar beet pulp (SBP), was evaluated. Our results showed that despite the absolute impact of these PCP mutations on pure pentose sugars, they are not as critical for growth of A. niger on more complex biomass substrates, such as WB and SBP. However, significant phenotypic variation was observed between the two biomass substrates, but also between the different PCP mutants. This shows that the high sugar heterogeneity of these substrates in combination with the high complexity and adaptability of the fungal sugar metabolism allow for activation of alternative strategies to support growth.

Characterization of Dissolved Organic Matter from Wildfire-induced Microcystis aeruginosa Blooms controlled by Copper Sulfate as Disinfection Byproduct Precursors Using APPI(-) and ESI(-) FT-ICR MS.

Copper-based algaecides are usually used for controlling algae bloom triggered by the elevated levels of nutrients after wildfires, resulting in the promoted reactivity of dissolved organic matter (DOM) in forming disinfectant byproducts (DBPs). To identify the best strategy for handling this source water, we employed Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to characterize the DBPs precursors after 4-d Microcystis aeruginosa bloom cultured with black (BE) and white (WE) ash water extracts under 0, 0.5, and 1.0 mg-Cu/L. The disappeared DOM during disinfections, primarily composed of O1-14, N1O1-14 and N2O1-14, had a higher average molecular weight (MW) and double-bond equivalent (DBE), relative to DOM after incubation, regardless of disinfects and Cu2+. This result suggests assigned features with larger MW and more double bonds/rings as preferable DBP precursors. We observed a larger number of disappeared assigned features with low DBE of 1-10 in control without Cu2+ addition, possibly explaining lower DOM chlorine reactivity in forming carbonaceous and oxygenated DBPs, relative to the treatments with Cu2+ addition. We found a larger number of O1-14 and N1O1-14 with DBE=5-16 in the treatments, potentially explaining higher DOM chloramine reactivity in forming N-nitrosodimethylamine (NDMA), compared to the control. Our study suggests removing oxygen- and nitrogen-containing organic compounds with more double bonds/aromatic rings as a preferable strategy for handling source water after controlling post-fire algae blooms with copper sulfate.

Mutual Interactions between Reduced Fe-Bearing Clay Minerals and Humic Acids under Dark, Oxygenated Conditions: Hydroxyl Radical Generation and Humic Acid Transformation.

Hydroxyl radicals (·OH) exert a strong impact on the carbon cycle due to their nonselective and highly oxidizing nature. Reduced iron-containing clay minerals (RIC) are one of the major contributors to the formation of ·OH in dark environments, but their interactions with humic acids (HA) are poorly known. Here, we investigate the mutual interactions between RIC and HA under dark and oxygenated conditions. HA decreased the oxidation rate of structural Fe(II) in RIC but significantly promoted the ·OH yield. HA dissolved a fraction of Fe(II) from RIC to form an aqueous Fe(II)-HA complex. ·OH were generated through both heterogeneous (through oxidation of structural Fe(II)) and homogeneous pathways (through oxidation of aqueous Fe(II)-HA species). RIC-mediated ·OH production by providing H2O2 to react with Fe(II)-HA and electrons to regenerate Fe(II)-HA. This highly efficient homogeneous pathway was responsible for increased ·OH yield. Abundant ·OH significantly decreased the molecular size, bleached chromophores, and increased the oxygen-containing functional groups of HA. These molecular changes of HA resembled photochemical transformation of HA. The mutual interaction between RIC and HA in dark and redox-fluctuating environments provides a new pathway for fast turnover of recalcitrant organic matters in clay- and HA-rich ecosystems such as tropical forest soils and tidal marsh sediments.

Potential utilization of terrestrially derived dissolved organic matter by aquatic microbial communities in saline lakes.

Lakes receive large amounts of terrestrially derived dissolved organic matter (tDOM). However, little is known about how aquatic microbial communities interact with tDOM in lakes. Here, by performing microcosm experiments we investigated how microbial community responded to tDOM influx in six Tibetan lakes of different salinities (ranging from 1 to 358 g/l). In response to tDOM addition, microbial biomass increased while dissolved organic carbon (DOC) decreased. The amount of DOC decrease did not show any significant correlation with salinity. However, salinity influenced tDOM transformation, i.e., microbial communities from higher salinity lakes exhibited a stronger ability to utilize tDOM of high carbon numbers than those from lower salinity. Abundant taxa and copiotrophs were actively involved in tDOM transformation, suggesting their vital roles in lacustrine carbon cycle. Network analysis indicated that 66 operational taxonomic units (OTUs, affiliated with Alphaproteobacteria, Actinobacteria, Bacteroidia, Bacilli,  Gammaproteobacteria, Halobacteria, Planctomycetacia, Rhodothermia, and Verrucomicrobiae) were associated with degradation of CHO compounds, while four bacterial OTUs (affiliated with Actinobacteria, Alphaproteobacteria, Bacteroidia and Gammaproteobacteria) were highly associated with the degradation of CHOS compounds. Network analysis further revealed that tDOM transformation may be a synergestic process, involving cooperation among multiple species. In summary, our study provides new insights into a microbial role in transforming tDOM in saline lakes and has important implications for understanding the carbon cycle in aquatic environments.

Single-Cell Metabolic Profiling: Metabolite Formulas from Isotopic Fine Structures in Heterogeneous Plant Cell Populations.

Characterization of the metabolic heterogeneity in cell populations requires the analysis of single cells. Most current methods in single-cell analysis rely on cell manipulation, potentially altering the abundance of metabolites in individual cells. A small sample volume and the chemical diversity of metabolites are additional challenges in single-cell metabolomics. Here, we describe the combination of fiber-based laser ablation electrospray ionization (f-LAESI) with 21 T Fourier transform ion cyclotron resonance mass spectrometry (21TFTICR-MS) for in situ single-cell metabolic profiling in plant tissue. Single plant cells infected by bacteria were selected and sampled directly from the tissue without cell manipulation through mid-infrared ablation with a fine optical fiber tip for ionization by f-LAESI. Ultrahigh performance 21T-FTICR-MS enabled the simultaneous capture of isotopic fine structures (IFSs) for 47 known and 11 unknown compounds, thus elucidating their elemental compositions from single cells and providing information on metabolic heterogeneity in the cell population.

Multiple biomarkers highlight the importance of water column processes in treatment wetland organic matter cycling.

A suite of biomarkers, including amino acids, pigments, and lignin phenols coupled with high resolution mass spectrometry were used to evaluate differences in the sources and fate of organic matter (OM) in Everglades treatment wetlands as a model for OM cycling in shallow water wetlands. Five components of the system (water column particulate matter, vertical traps, flocculent material, periphyton, and surface soil) were assessed for OM transformations down-profile (i.e. water column to soil) and between treatment cells dominated by emergent aquatic vegetation (EAV) and submerged aquatic vegetation (SAV), with comparisons to reference sites within the remnant Everglades. We found that OM cycling is fundamentally different between EAV and SAV wetlands, and that SAV wetlands have some shared characteristics with similar habitats in the remnant Everglades. Other than locations densely populated by Typha spp., water column particulate organic C was predominantly derived from microbial/cryptomonad sources, rather than macroscopic sources (vascular plants and algal mats). Bacterial amino acid biomarkers were positively correlated with amino acid degradation indices and organic P (Po), respectively suggesting that microbial abundance is associated with less degraded OM, and that further investigation into relationships between microbial biomass and Po is warranted. Overall, this multi-biomarker approach can elucidate the relative degradation of OM pools, identify sources of OM, and highlight the importance of water column processes in shallow water wetlands.

Untargeted metabolomic profiling of Sphagnum fallax reveals novel antimicrobial metabolites.

Sphagnum mosses dominate peatlands by employing harsh ecosystem tactics to prevent vascular plant growth and microbial degradation of these large carbon stores. Knowledge about Sphagnum-produced metabolites, their structure and their function, is important to better understand the mechanisms, underlying this carbon sequestration phenomenon in the face of climate variability. It is currently unclear which compounds are responsible for inhibition of organic matter decomposition and the mechanisms by which this inhibition occurs. Metabolite profiling of Sphagnum fallax was performed using two types of mass spectrometry (MS) systems and 1H nuclear magnetic resonance spectroscopy (1H NMR). Lipidome profiling was performed using LC-MS/MS. A total of 655 metabolites, including one hundred fifty-two lipids, were detected by NMR and LC-MS/MS-329 of which were novel metabolites (31 unknown lipids). Sphagum fallax metabolite profile was composed mainly of acid-like and flavonoid glycoside compounds, that could be acting as potent antimicrobial compounds, allowing Sphagnum to control its environment. Sphagnum fallax metabolite composition comparison against previously known antimicrobial plant metabolites confirmed this trend, with seventeen antimicrobial compounds discovered to be present in Sphagnum fallax, the majority of which were acids and glycosides. Biological activity of these compounds needs to be further tested to confirm antimicrobial qualities. Three fungal metabolites were identified providing insights into fungal colonization that may benefit Sphagnum. Characterizing the metabolite profile of Sphagnum fallax provided a baseline to understand the mechanisms in which Sphagnum fallax acts on its environment, its relation to carbon sequestration in peatlands, and provide key biomarkers to predict peatland C store changes (sequestration, emissions) as climate shifts.

Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples.

The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.

Online supercritical fluid extraction mass spectrometry (SFE-LC-FTMS) for sensitive characterization of soil organic matter.

We report a novel technical approach for subcritical fluid extraction (SFE) for organic matter characterization in complex matrices such as soil. The custom platform combines on-line SFE with micro-solid phase extraction, nano liquid chromatography (LC), electrospray ionization and Fourier transform mass spectrometry (SFE-LC-FTMS). We demonstrated the utility of SFE-LC-FTMS, including results from both Orbitrap and FTICR MS, for analysis of complex mixtures of organic compounds in a solid matrix by characterizing soil organic matter in peat, a high-carbon soil. For example, in a single experiment, >6000 molecular formulas can be assigned based upon FTICR MS data from 1-50 µL of soil samples (roughly 1-50 mg of soil, dependent on soil density), nearly twice that typically obtained from direct infusion liquid solvent extraction (LSE) from an order of magnitude larger volume of the same soil. The detected species consisted predominately of lipid-like, lignin-like and protein-like compounds, based on their O/C and H/C ratios, with predominantly CHO and CHONP molecular compositions. These results clearly demonstrate that SFE has the potential to effectively extract a variety of molecular species and could become an important member of a suite of extraction methods for studying SOM and other natural organic matter. This is especially true when comprehensive coverage, minimal sample volumes, and high sensitivity are required, or when the presence of organic solvent residue in residual soil is problematic. The SFE based extraction protocol could potentially enable spatially resolved characterization of organic matter in soil with a resolution of ∼1 mm3 to facilitate studies probing the spatial heterogeneity of soil.

Author Correction: Informed-Proteomics: open-source software package for top-down proteomics.

In the version of this article initially published, the authors erroneously reported the search mode that was used for ProSightPC 3.0 in the Online Methods and in Supplementary Table 3.

Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms.

van Krevelen diagrams (O/C vs H/C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O/C and H/C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O/C vs H/C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classification for biological samples analyzed by high-resolution mass spectrometry based on an assessment of the C/H/O/N/P stoichiometric ratios of over 130 000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino sugars, carbohydrates, nucleotides, and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a signficant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to improve our understanding of the ecosystem structure and function through the chemical characterization of biological samples.

Molecular Insights into Arctic Soil Organic Matter Degradation under Warming.

Molecular composition of the Arctic soil organic carbon (SOC) and its susceptibility to microbial degradation are uncertain due to heterogeneity and unknown SOC compositions. Using ultrahigh-resolution mass spectrometry, we determined the susceptibility and compositional changes of extractable dissolved organic matter (EDOM) in an anoxic warming incubation experiment (up to 122 days) with a tundra soil from Alaska (United States). EDOM was extracted with 10 mM NH4HCO3 from both the organic- and mineral-layer soils during incubation at both -2 and 8 °C. Based on their O:C and H:C ratios, EDOM molecular formulas were qualitatively grouped into nine biochemical classes of compounds, among which lignin-like compounds dominated both the organic and the mineral soils and were the most stable, whereas amino sugars, peptides, and carbohydrate-like compounds were the most biologically labile. These results corresponded with shifts in EDOM elemental composition in which the ratios of O:C and N:C decreased, while the average C content in EDOM, molecular mass, and aromaticity increased after 122 days of incubation. This research demonstrates that certain EDOM components, such as amino sugars, peptides, and carbohydrate-like compounds, are disproportionately more susceptible to microbial degradation than others in the soil, and these results should be considered in SOC degradation models to improve predictions of Arctic climate feedbacks.

Formularity: Software for Automated Formula Assignment of Natural and Other Organic Matter from Ultrahigh-Resolution Mass Spectra.

Ultrahigh resolution mass spectrometry, such as Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), can resolve thousands of molecular ions in complex organic matrices. A Compound Identification Algorithm (CIA) was previously developed for automated elemental formula assignment for natural organic matter (NOM). In this work, we describe software Formularity with a user-friendly interface for CIA function and newly developed search function Isotopic Pattern Algorithm (IPA). While CIA assigns elemental formulas for compounds containing C, H, O, N, S, and P, IPA is capable of assigning formulas for compounds containing other elements. We used halogenated organic compounds (HOC), a chemical class that is ubiquitous in nature as well as anthropogenic systems, as an example to demonstrate the capability of Formularity with IPA. A HOC standard mix was used to evaluate the identification confidence of IPA. Tap water and HOC spike in Suwannee River NOM were used to assess HOC identification in complex environmental samples. Strategies for reconciliation of CIA and IPA assignments were discussed. Software and sample databases with documentation are freely available.