1. Ionomics Senthil Natesan

2. Why ionome
• Living systems are supported and sustained by the genome through
the action of the transcriptome, proteome, metabolome, and
ionome, the four basic biochemical pillars of functional genomics.
• These pillars represent the sum of all the expressed
genes, proteins, metabolites, and elements within an organism.
• The dynamic response and interaction of these biochemical ‘‘omes’’
defines how a living system functions, and its study, systems
biology, is now one of the biggest challenges in the life sciences
• The ionome is involved in such a broad range of important
biological phenomena, including
electrophysiology, signaling, enzymology, osmoregulation, and
transport, its study promises to yield new and significant biological
insight.

3. What area it is covering ?
• Lahner and colleagues first described the ionome to include all the
metals, metalloids, and nonmetals present in an organism (Lahner et
al., 2003), extending the term metallome (Outten and O’Halloran, 2001;
Williams, 2001; Szpunar, 2004) to include biologically significant
nonmetals such as nitrogen, phosphorus, sulfur, selenium, chlorine, and
iodine.
• It is important to note here that the boundaries between the
ionome, metabolome, and proteome are blurred.
• Compounds containing the nonmetals phosphorus, sulfur, or nitrogen, for
example, would fall within both the ionome and metabolome, and metals
such as zinc, copper, manganese, and iron in metalloproteins would fall
within the proteome, or metalloproteome as it has been described
(Szpunar, 2004).
• The elements measured in the ionome will be determined by their
biological importance or environmental relevance, in conjunction with
their amenability to quantitation
David E. Salt 2004.Update on Plant Ionomics. Plant Physiology 136: 2451–2456

5. Ionome flow chart details
• Figure 1. High-throughput ionomics. Putative mutants and wild-type Arabidopsis plants are grown
together with known ionomic mutants, used as positive controls, under standardized conditions.
• Plants are uniformly sampled, digested in concentrated nitric acid, diluted, and analyzed for
numerous elements using ICP-MS.
• Raw ICP-MS data are normalized using analytical standards and calculated weights based on wild-
type plants (Lahner et al., 2003).
• Data are processed using custom tools and stored in a searchable,World WideWeb-accessible
database.
• Ionomic analysis can also be applied to other plants with available genetic resources, including rice
and maize.
• Elements in the Periodic Table highlighted in black boxes represent those elements analyzed during
our ionomic analyses using ICP-MS, elements highlighted in green are essential for plant
growth, and those in red represent nonessential trace elements.
• The table represents Arabidopsis (Col 0) shoot and seed ionomes, all elements presented as mg g21
dry weight. Data represent the average shoot concentrations from 60 individual plants and seed
from 12 individuals 6 SD as percentage of average (%RSD), all plants grown as described by Lahner
et al. (2003).
David E. Salt 2004.Update on Plant Ionomics. Plant Physiology 136: 2451–2456

6. Natural variation –Arabidopsis ionome
• Natural variation in Arabidopsis seed and shoot
phosphate accumulation is known to exist between the
Ler and Cvi accessions (Bentsink et al., 2003), and for
potassium, sodium, calcium, magnesium, iron, mangan
ese, zinc, and phosphorus in seeds of numerous
ecotypes (Vreugdenhil et al., 2004).
• Analyses of Ler/Cvi recombinant inbred lines revealed
quantitative trait loci (QTL) that explain between 10%
and 79% of this variation for the different elements
(Vreugdenhil et al., 2004). Natural variation in several
Arabidopsis ecotypes has also been observed for shoot
caesium
Baxter et al.2007 Purdue Ionomics Information Management System. An
Integrated Functional Genomics Platform. Plant Physiology, 143: 600–611

7. Does this mutation have an ionomic
phenotype?’
• Currently, PiiMS contains shoot ionomic data on over 7,500
unique Arabidopsis lines, including fastneutron, EMS, and
T-DNA-mutagenized lines, natural accessions, and RILs, of
which approximately 1,500 are available in the ABRC and
SIGnAL collections
• The database contains data on homozygous sequence
indexed T-DNA lines in over 1,000 unique genes.
• The lines include knockouts in transporters and kinases
selected by the Arabidopsis 2010 Ionomics group
(http://www.cbs.umn.edu/Arabidopsis/ionome), as well as
lines sent to us by other users interested in the ionomics
phenotype of knockouts in their genes of interest.

8. Inductively Coupled Plasma- Optical Emission
Spectroscopy (ICP-OES) technology behind
• The ICP is designed to generate a plasma, a gas in which atoms are present in the ionized state .
• To generate a plasma a silica torch is used, situated within a water- or argon-cooled coil of a radio
frequency generator (RF coil). Flowing gas (plasma gas) [typically argon (Ar)] is introduced into the
plasma torch and the radio frequency field ionizes the gas, making it electrically conductive.
• The plasma is maintained by the inductive heating of the flowing gas. The plasma, at up to 8000
K, is insulated both electrically and thermally from the instrument, and maintained in position by a
flow of cooling argon gas (coolant gas).
• The sample to be analyzed, as an aerosol, is carried into the plasma by a third argon gas stream
(carrier gas).
• A nebulizer in the instrument transforms the aqueous sample into an aerosol. The sample is
pumped into the nebulizer via a peristaltic pump where it is converted into an aerosol, which
passes into the spray chamber with the carrier argon gas.
• In the spray chamber the finest sample droplets are swept into the plasma while the large sample
droplets settle out and run to waste
• Onintroduction into the plasma atoms in the sample are ionized, generally into singly charged
positive ions. Once ionized the analyte atoms are detected using either an optical emission
spectrometer or a mass spectrometer.
Salt et al .2008 Ionomics and the Study of the Plant Ionome .
Annu. Rev. Plant Biol. 59:709–33

9. Inductively Coupled Plasma
Mass Spectrometry (ICP-MS) Vs ( ICP-OES)
• Advantage of ICP-MS over ICP-OES is that it allows for a smaller
sample size owing to its greater sensitivity.
• Although ICPOES is less sensitive than ICP-MS, some of this
sensitivity is won back by the robustness of ICP-OES in more
concentrated sample matrices.
• Whereas ICP-MS struggles with sample matrices with greater than
about 0.1% solids, ICP-OES can handle up to about 3% dissolved
solids
• Drawbacks of ICP-MS is that the formation of polyatomic ionic
species in the plasma can interfere with the measurement of
particular elements; e.g., 40Ar16O+ interferes with the
determination of 56Fe.
• An alternative approach to the removal or reduction of interfering
polyatomic ions is to utilize a single collector magnetic sector high-
resolution ICP-MS (HR-ICP-MS).
Salt et al .2008 Ionomics and the Study of the Plant Ionome .
Annu. Rev. Plant Biol. 59:709–33

10. ICP-MS Analysis
• eLaboratory portal, PiiMS divides the Purdue Ionomics pipeline into
four process stages defined as Planting, Harvesting, Drying, and MS
Analysis .
• These processes can be generalized as experimental
subject, sample acquisition, sample preparation, and sample
analysis. Samples are first prepared for ICP-MS analysis by drying
and digestion in acid.
• The concentrations of various elements in the sample are then
quantified using ICP-MS. Within the eManagement portal, there are
tools to define the list of elements to be analyzed, providing full
flexibility in the analysis.
• ICP-MS analyst is satisfied with the quality of the data, it is released
into the database for general searching and visualization.
Baxter et al.2007 Purdue Ionomics Information Management System. An
Integrated Functional Genomics Platform. Plant Physiology, 143: 600–611

13. Baxter et al.2007 Purdue Ionomics Information Management System. An
Integrated Functional Genomics Platform. Plant Physiology, 143: 600–611

15. Purdue Ionomics Information Management
System (PiiMS) www.purdue.edu/dp/ionomics
• PiiMS currently contains data on shoot concentrations of
P, Ca, K, Mg, Cu, Fe, Zn, Mn, Co, Ni, B, Se, Mo, Na, As, and Cd in over
60,000 shoot tissue samples of Arabidopsis (Arabidopsis
thaliana), including ethyl methanesulfonate, fast-neutron and
defined T-DNA mutants
• Natural accession and populations of recombinant inbred lines from
over 800 separate experiments, representing over 1,000,000 fully
quantitative elemental concentrations.
• Using Web services, we also plan to integrate the PiiMS ionomics
dataset with other Arabidopsis resources.
• Finally, we are taking the basic architectural principles of PiiMS and
generalizing them across other organisms, including rice (Oryza
sativa) and yeast (Saccharomyces cerevisiae), as well as other omics
technologies, including proteomics and metabolomics
Salt, 2004.Update on Plant Ionomics. Plant Physiology 136: 2451–2456

16. Applications
• Once ionomics QTL have been identified, genomic tools available
for A. thaliana and to some extent rice and maize can be used to
locate the genes that underlie these QTL and thus describe the
traits at a molecular level
• Genes responsible for QTL that control Na in rice and A. thaliana ;
interestingly, the responsible gene was found to be the Na-
transporter HKT1 in both species.
• Loudet et al. recently identified the gene that controls a major QTL
for sulfate accumulation in A. thalianaadenosine 5-phosphosulfate
reductase, a central enzyme in sulfate assimilation.
• Researchers are also well on the way to identifying the gene that
controls a major QTL for seed P content in A. thaliana, which has
currently been narrowed down to only 13 open reading frames
Salt et al .2008 Ionomics and the Study of the Plant Ionome .
Annu. Rev. Plant Biol. 59:709–33