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At least 127 records · Page 7Linked to original sources

PubMed2006

Community annotation: procedures, protocols, and supporting tools.

Investigators at the Baylor College of Medicine Human Genome Sequencing Center (BCM-HGSC) and BeeBase organized a community-wide effort to manually annotate the honey bee (Apis mellifera) genome. Although various strategies for manual annotation have been used in the past, the value of dispersed community annotation has not yet been demonstrated. Here we make a case for the merit of dispersed community annotation. We present annotation procedures, standard protocols, and tools used for sequence analysis, data submission, and data management. We also report lessons learned from this dispersed community annotation effort for a metazoan genome.

Animals↗

PubMed2003

Reevaluating human gene annotation: a second-generation analysis of chromosome 22.

We report a second-generation gene annotation of human chromosome 22. Using expressed sequence databases, comparative sequence analysis, and experimental verification, we have extended genes, fused previously fragmented structures, and identified new genes. The total length in exons of annotation was increased by 74% over our previously published annotation and includes 546 protein-coding genes and 234 pseudogenes. Thirty-two potential protein-coding annotations are partial copies of other genes, and may represent duplications on an evolutionary path to change or loss of function. We also identified 31 non-protein-coding transcripts, including 16 possible antisense RNAs. By extrapolation, we estimate the human genome contains 29,000-36,000 protein-coding genes, 21,300 pseudogenes, and 1500 antisense RNAs. We suggest that our revised annotation criteria provide a paradigm for future annotation of the human genome.

Animals↗

PubMed2002

Holter recordings with continuous marker annotation to evaluate pacemaker function.

BACKGROUND: Pacemaker marker annotations facilitate the interpretation of device behavior in addition to ECG recordings. However, they are only available in conjunction with a programmer. We studied the diagnostic value of a prototype Telemetry Holter Decoder (THD), providing continuous marker annotations on a conventional Holter. METHODS: The study included 20 patients with VDD or DDDR pacemakers. A 24-hour Holter was performed using the THD. Marker annotations are transmitted from the pacemaker to the THD, which transforms them into analog signals, which are recorded on one of the Holter channels. RESULTS: During a total recording time of 458 hours, high quality marker annotations were retrieved for every patient. Artefacts disturbed the recordings during 184 min (0.67%). The THD provided information not discernible on the ECG: intermittent atrial undersensing during sinus rhythm (1096 times). Atrial tachycardias, not visible on the ECG, were detected in 2 patients. The activation of tachycardia response algorithms was clearly annotated in 11,516 events. A total of 8875 PVC's occurred, 57.8% of which were classified incorrectly in the event counters as conducted or fusion beats. Atrial far-field sensing or VA conduction was demonstrated 4294 times. Electromagnetic interferences, not visible on the ECG, could be seen three times. CONCLUSION: Recording of continuous high-quality marker annotation on a conventional Holter is feasible. The THD provides important information on device behavior, even in patients assumed to have regular device function, and shows to be clearly superior to ECG interpretation alone. Such data can be used for improved programming, troubleshooting and for the validation of new algorithms.

Aged↗

PubMed2002

Visualizing the genome: techniques for presenting human genome data and annotations.

BACKGROUND: In order to take full advantage of the newly available public human genome sequence data and associated annotations, biologists require visualization tools ("genome browsers") that can accommodate the high frequency of alternative splicing in human genes and other complexities. RESULTS: In this article, we describe visualization techniques for presenting human genomic sequence data and annotations in an interactive, graphical format. These techniques include: one-dimensional, semantic zooming to show sequence data alongside gene structures; color-coding exons to indicate frame of translation; adjustable, moveable tiers to permit easier inspection of a genomic scene; and display of protein annotations alongside gene structures to show how alternative splicing impacts protein structure and function. These techniques are illustrated using examples from two genome browser applications: the Neomorphic GeneViewer annotation tool and ProtAnnot, a prototype viewer which shows protein annotations in the context of genomic sequence. CONCLUSION: By presenting techniques for visualizing genomic data, we hope to provide interested software developers with a guide to what features are most likely to meet the needs of biologists as they seek to make sense of the rapidly expanding body of public genomic data and annotations.

Alternative Splicing↗

PubMed2004

BioBuilder as a database development and functional annotation platform for proteins.

BACKGROUND: The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. RESULTS: BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database http://www.hprd.org, a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. CONCLUSIONS: As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL.

Computational Biology↗

PubMed2005

MILANO--custom annotation of microarray results using automatic literature searches.

BACKGROUND: High-throughput genomic research tools are becoming standard in the biologist's toolbox. After processing the genomic data with one of the many available statistical algorithms to identify statistically significant genes, these genes need to be further analyzed for biological significance in light of all the existing knowledge. Literature mining--the process of representing literature data in a fashion that is easy to relate to genomic data--is one solution to this problem. RESULTS: We present a web-based tool, MILANO (Microarray Literature-based Annotation), that allows annotation of lists of genes derived from microarray results by user defined terms. Our annotation strategy is based on counting the number of literature co-occurrences of each gene on the list with a user defined term. This strategy allows the customization of the annotation procedure and thus overcomes one of the major limitations of the functional annotations usually provided with microarray results. MILANO expands the gene names to include all their informative synonyms while filtering out gene symbols that are likely to be less informative as literature searching terms. MILANO supports searching two literature databases: GeneRIF and Medline (through PubMed), allowing retrieval of both quick and comprehensive results. We demonstrate MILANO's ability to improve microarray analysis by analyzing a list of 150 genes that were affected by p53 overproduction. This analysis reveals that MILANO enables immediate identification of known p53 target genes on this list and assists in sorting the list into genes known to be involved in p53 related pathways, apoptosis and cell cycle arrest. CONCLUSIONS: MILANO provides a useful tool for the automatic custom annotation of microarray results which is based on all the available literature. MILANO has two major advances over similar tools: the ability to expand gene names to include all their informative synonyms while removing synonyms that are not informative and access to the GeneRIF database which provides short summaries of curated articles relevant to known genes. MILANO is available at http://milano.md.huji.ac.il.

Algorithms↗

PubMed2005

AutoFACT: an automatic functional annotation and classification tool.

BACKGROUND: Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. RESULTS: We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1-2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. CONCLUSION: AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at http://megasun.bch.umontreal.ca/Software/AutoFACT.htm.

Acanthamoeba castellanii↗

PubMed2005

FIGENIX: intelligent automation of genomic annotation: expertise integration in a new software platform.

BACKGROUND: Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes' position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps. RESULTS: Here we propose an innovative automated platform, FIGENIX, which includes an expert system capable to substitute to human expertise at several key steps. FIGENIX currently automates complex pipelines of structural and functional annotation under the supervision of the expert system (which allows for example to make key decisions, check intermediate results or refine the dataset). The quality of the results produced by FIGENIX is comparable to those obtained by expert biologists with a drastic gain in terms of time costs and avoidance of errors due to the human manipulation of data. CONCLUSION: The core engine and expert system of the FIGENIX platform currently handle complex annotation processes of broad interest for the genomic community. They could be easily adapted to new, or more specialized pipelines, such as for example the annotation of miRNAs, the classification of complex multigenic families, annotation of regulatory elements and other genomic features of interest.

Automation↗

PubMed2005

Clustering the annotation space of proteins.

BACKGROUND: Current protein clustering methods rely on either sequence or functional similarities between proteins, thereby limiting inferences to one of these areas. RESULTS: Here we report a new approach, named CLAN, which clusters proteins according to both annotation and sequence similarity. This approach is extremely fast, clustering the complete SwissProt database within minutes. It is also accurate, recovering consistent protein families agreeing on average in more than 97% with sequence-based protein families from Pfam. Discrepancies between sequence- and annotation-based clusters were scrutinized and the reasons reported. We demonstrate examples for each of these cases, and thoroughly discuss an example of a propagated error in SwissProt: a vacuolar ATPase subunit M9.2 erroneously annotated as vacuolar ATP synthase subunit H. CLAN algorithm is available from the authors and the CLAN database is accessible at http://maine.ebi.ac.uk:8000/cgi-bin/clan/ClanSearch.pl CONCLUSIONS: CLAN creates refined function-and-sequence specific protein families that can be used for identification and annotation of unknown family members. It also allows easy identification of erroneous annotations by spotting inconsistencies between similarities on annotation and sequence levels.

Adenosine Triphosphatases↗

PubMed2005

A sentence sliding window approach to extract protein annotations from biomedical articles.

BACKGROUND: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations. RESULTS: The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of correct extractions of individual entities (i.e. proteins and GO terms) involved in the relationships used for the annotations was significantly higher than the correct extractions of the complete annotations (protein-function relations). CONCLUSION: We explored the use of averaging sentence sliding windows for information extraction, especially in a context where conventional training data is unavailable. The combination of our approach with more refined statistical estimators and machine learning techniques might be a way to improve annotation extraction for future biomedical text mining applications.

Biomedical Research↗

PubMed2005

Protein annotation as term categorization in the gene ontology using word proximity networks.

BACKGROUND: We participated in the BioCreAtIvE Task 2, which addressed the annotation of proteins into the Gene Ontology (GO) based on the text of a given document and the selection of evidence text from the document justifying that annotation. We approached the task utilizing several combinations of two distinct methods: an unsupervised algorithm for expanding words associated with GO nodes, and an annotation methodology which treats annotation as categorization of terms from a protein's document neighborhood into the GO. RESULTS: The evaluation results indicate that the method for expanding words associated with GO nodes is quite powerful; we were able to successfully select appropriate evidence text for a given annotation in 38% of Task 2.1 queries by building on this method. The term categorization methodology achieved a precision of 16% for annotation within the correct extended family in Task 2.2, though we show through subsequent analysis that this can be improved with a different parameter setting. Our architecture proved not to be very successful on the evidence text component of the task, in the configuration used to generate the submitted results. CONCLUSION: The initial results show promise for both of the methods we explored, and we are planning to integrate the methods more closely to achieve better results overall.

Databases, Genetic↗

PubMed2006

Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration.

BACKGROUND: There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences. RESULTS: Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant. CONCLUSION: Gene annotating remains an ongoing and challenging task that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become more precisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualize sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.

Alternative Splicing↗

PubMed2006

TreeDyn: towards dynamic graphics and annotations for analyses of trees.

BACKGROUND: Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees. RESULTS: We have developed TreeDyn, a tool using annotations and dynamic graphical methods for editing and analyzing multiple trees. The main features of TreeDyn are 1) the management of multiple windows and multiple trees per window, 2) the export of graphics to several standard file formats with or without HTML encapsulation and a new format called TGF, which enables saving and restoring graphical analysis, 3) the projection of texts or symbols facing leaf labels or linked to nodes, through manual pasting or by using annotation files, 4) the highlight of graphical elements after querying leaf labels (or annotations) or by selection of graphical elements and information extraction, 5) the highlight of targeted trees according to a source tree browsed by the user, 6) powerful scripts for automating repetitive graphical tasks, 7) a command line interpreter enabling the use of TreeDyn through CGI scripts for online building of trees, 8) the inclusion of a library of packages dedicated to specific research fields involving trees. CONCLUSION: TreeDyn is a tree visualization and annotation tool which includes tools for tree manipulation and annotation and uses meta-information through dynamic graphical operators or scripting to help analyses and annotations of single trees or tree collections.

Computer Graphics↗

PubMed2004

FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression.

BACKGROUND: While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes. RESULTS: We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P < 0.001) enrichment in genes associated with amine metabolism. CONCLUSION: The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.

Animals↗

PubMed2007

Experimental validation of novel genes predicted in the un-annotated regions of the Arabidopsis genome.

BACKGROUND: Several lines of evidence support the existence of novel genes and other transcribed units which have not yet been annotated in the Arabidopsis genome. Two gene prediction programs which make use of comparative genomic analysis, Twinscan and EuGene, have recently been deployed on the Arabidopsis genome. The ability of these programs to make use of sequence data from other species has allowed both Twinscan and EuGene to predict over 1000 genes that are intergenic with respect to the most recent annotation release. A high throughput RACE pipeline was utilized in an attempt to verify the structure and expression of these novel genes. RESULTS: 1,071 un-annotated loci were targeted by RACE, and full length sequence coverage was obtained for 35% of the targeted genes. We have verified the structure and expression of 378 genes that were not present within the most recent release of the Arabidopsis genome annotation. These 378 genes represent a structurally diverse set of transcripts and encode a functionally diverse set of proteins. CONCLUSION: We have investigated the accuracy of the Twinscan and EuGene gene prediction programs and found them to be reliable predictors of gene structure in Arabidopsis. Several hundred previously un-annotated genes were validated by this work. Based upon this information derived from these efforts it is likely that the Arabidopsis genome annotation continues to overlook several hundred protein coding genes.

Arabidopsis↗

PubMed2002

Annotation of the Drosophila melanogaster euchromatic genome: a systematic review.

BACKGROUND: The recent completion of the Drosophila melanogaster genomic sequence to high quality and the availability of a greatly expanded set of Drosophila cDNA sequences, aligning to 78% of the predicted euchromatic genes, afforded FlyBase the opportunity to significantly improve genomic annotations. We made the annotation process more rigorous by inspecting each gene visually, utilizing a comprehensive set of curation rules, requiring traceable evidence for each gene model, and comparing each predicted peptide to SWISS-PROT and TrEMBL sequences. RESULTS: Although the number of predicted protein-coding genes in Drosophila remains essentially unchanged, the revised annotation significantly improves gene models, resulting in structural changes to 85% of the transcripts and 45% of the predicted proteins. We annotated transposable elements and non-protein-coding RNAs as new features, and extended the annotation of untranslated (UTR) sequences and alternative transcripts to include more than 70% and 20% of genes, respectively. Finally, cDNA sequence provided evidence for dicistronic transcripts, neighboring genes with overlapping UTRs on the same DNA sequence strand, alternatively spliced genes that encode distinct, non-overlapping peptides, and numerous nested genes. CONCLUSIONS: Identification of so many unusual gene models not only suggests that some mechanisms for gene regulation are more prevalent than previously believed, but also underscores the complex challenges of eukaryotic gene prediction. At present, experimental data and human curation remain essential to generate high-quality genome annotations.

Animals↗

PubMed2006

Automatic annotation of eukaryotic genes, pseudogenes and promoters.

BACKGROUND: The ENCODE gene prediction workshop (EGASP) has been organized to evaluate how well state-of-the-art automatic gene finding methods are able to reproduce the manual and experimental gene annotation of the human genome. We have used Softberry gene finding software to predict genes, pseudogenes and promoters in 44 selected ENCODE sequences representing approximately 1% (30 Mb) of the human genome. Predictions of gene finding programs were evaluated in terms of their ability to reproduce the ENCODE-HAVANA annotation. RESULTS: The Fgenesh++ gene prediction pipeline can identify 91% of coding nucleotides with a specificity of 90%. Our automatic pseudogene finder (PSF program) found 90% of the manually annotated pseudogenes and some new ones. The Fprom promoter prediction program identifies 80% of TATA promoters sequences with one false positive prediction per 2,000 base-pairs (bp) and 50% of TATA-less promoters with one false positive prediction per 650 bp. It can be used to identify transcription start sites upstream of annotated coding parts of genes found by gene prediction software. CONCLUSION: We review our software and underlying methods for identifying these three important structural and functional genome components and discuss the accuracy of predictions, recent advances and open problems in annotating genomic sequences. We have demonstrated that our methods can be effectively used for initial automatic annotation of the eukaryotic genome.

Animals↗

PubMed1997

The comparative metabolism of the mollicutes (Mycoplasmas): the utility for taxonomic classification and the relationship of putative gene annotation and phylogeny to enzymatic function in the smallest free-living cells.

Mollicutes or mycoplasmas are a class of wall-less bacteria descended from low G + C% Gram-positive bacteria. Some are exceedingly small, about 0.2 micron in diameter, and are examples of the smallest free-living cells known. Their genomes are equally small; the smallest in Mycoplasma genitalium is sequenced and is 0.58 mb with 475 ORFs, compared with 4.639 mb and 4288 ORFs for Escherichia coli. Because of their size and apparently limited metabolic potential, Mollicutes are models for describing the minimal metabolism necessary to sustain independent life. Mollicutes have no cytochromes or the TCA cycle except for malate dehydrogenase activity. Some uniquely require cholesterol for growth, some require urea and some are anaerobic. They fix CO2 in anaplerotic or replenishing reactions. Some require pyrophosphate not ATP as an energy source for reactions, including the rate-limiting step of glycolysis: 6-phosphofructokinase. They scavenge for nucleic acid precursors and apparently do not synthesize pyrimidines or purines de novo. Some genera uniquely lack dUTPase activity and some species also lack uracil-DNA glycosylase. The absence of the latter two reactions that limit the incorporation of uracil or remove it from DNA may be related to the marked mutability of the Mollicutes and their tachytelic or rapid evolution. Approximately 150 cytoplasmic activities have been identified in these organisms, 225 to 250 are presumed to be present. About 100 of the core reactions are graphically linked in a metabolic map, including glycolysis, pentose phosphate pathway, arginine dihydrolase pathway, transamination, and purine, pyrimidine, and lipid metabolism. Reaction sequences or loci of particular importance are also described: phosphofructokinases, NADH oxidase, thioredoxin complex, deoxyribose-5-phosphate aldolase, and lactate, malate, and glutamate dehydrogenases. Enzymatic activities of the Mollicutes are grouped according to metabolic similarities that are taxonomically discriminating. The arrangements attempt to follow phylogenetic relationships. The relationships of putative gene assignments and enzymatic function in My. genitalium, My. pneumoniae, and My. capricolum subsp. capricolum are specially analyzed. The data are arranged in four tables. One associates gene annotations with congruent reports of the enzymatic activity in these same Mollicutes, and hence confirms the annotations. Another associates putative annotations with reports of the enzyme activity but from different Mollicutes. A third identifies the discrepancies represented by those enzymatic activities found in Mollicutes with sequenced genomes but without any similarly annotated ORF. This suggests that the gene sequence is significantly different from those already deposited in the databanks and putatively annotated with the same function. Another comparison lists those enzymatic activities that are both undetected in Mollicutes and not associated with any ORF. Evidence is presented supporting the theory that there are relatively small gene sequences that code for functional centers of multiple enzymatic activity. This property is seemingly advantageous for an organism with a small genome and perhaps under some coding restraint. The data suggest that a concept of "remnant" or "useless genes" or "useless enzymes" should be considered when examining the relationship of gene annotation and enzymatic function. It also suggests that genes in addition to representing what cells are doing or what they may do, may also identify what they once might have done and may never do again.

Adenosine Triphosphate↗