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Development of non-invasive stress biomarkers in octopusesRachel ThompsonJune 1, 2009
Abstract
Octopuses are an important part of the Pacific Northwest ecosystem. Recently,
local populations have been experiencing declines due to pollution and large-scale
climate processes. Non-invasive sampling techniques were developed in an attempt to
characterize the physiological condition of adult octopuses in a controlled environment.
Potential biomarkers of stress (proteins in epidermal mucus and behavior patterns) were
identified, and could be useful in identifying a stressed state in an octopus in the wild or
in captivity. Larval developmental patterns were established by analysis of the expression
of two important developmental genes, orthodenticle-like protein and hedgehog. This
study serves to provide researchers and aquarists with baseline physiological data that
could be used to identify a stressed state in an adult octopus, or an altered developmental
pattern in larvae, using techniques that are less invasive than hemolymph or tissue
sampling.
Introduction
Octopuses are advanced invertebrates with a strong tie with the Pacific Northwest.
Two local species are the Red Octopus (Octopus rubescens) and the Giant Pacific
Octopus (Enteroctopus dofleini). Both are benthic species, with ranges along the Eastern
Pacific Ocean from Mexico to Alaska. Recently, populations have been declining due to
several factors, including pollution and large-scale climate processes affecting the Puget
Sound region (Rigby et al. 2005, Villanueva and Norman 2008). Octopus species are
important prey items for higher predators in Puget Sound. Their conservation is essential
to the maintenance of the region’s trophic structure (Onthank and Cowles 2008).
Octopuses are oviparous organisms that brood and care for their eggs during
development (Kaneko et al. 2006). Red Octopus larvae hatch approximately 6 to 8 weeks
after they are laid, and enter the water column as planktonic predators (von Boletzky
2003). The timing and success of development is dramatically affected by environmental
variables, such as changes in temperature and exposure the chemicals (Clarke et al.
2009). In a laboratory setting, increased temperatures (to 23 degrees Celsius from 18
degrees Celsius) accelerated the development of octopus hatchlings, and shortened their
life spans by up to 20% (Forsythe et al. 1988). The effect on adult octopuses has yet to be
determined. However, as cephalopods are poikilothermic organisms, their physiology
during all life stages is dramatically influenced by water temperature. The challenge lies
in identifying and quantifying these influences.
Responses to stress in octopuses can be obvious, such as color changing when
faced by a predator, but indicators of chemical or temperature stress are not often visual.
Stress can impair immune function in many invertebrates, leading to decreased disease
resistance (Malham et al. 2003). The cephalopod immune system consists of humoral and
cellular mechanisms (Ford 1992). The common stress response of animals is intended to
maintain homeostasis when threatened by an environmental change. In cephalopods, this
response releases catecholamines into the hemolymph, which shut down body functions
related to growth, reproduction and immunity with the intent of allocating energy
resources towards more immediate concerns (Malham et al. 2002). Specific effects of
stressors, such as exposure to air, include decreased hemocyte counts, and a decrease in
phagocytotic activity in those remaining cells. Since immune defenses are down-
regulated in this manner while the animal is in a stressed condition, it is left more
susceptible to disease.
The introduction of temperature and chemical stressors can have significant
effects on the physiology of aquatic organisms, including but not limited to, disruption of
development, reproduction and growth (Zala and Penn 2004). It has also been found that
exposure to chemical pollution, specifically endocrine-disrupting chemicals (EDCs), such
as those found in urbanized areas of the Puget Sound, can result in abnormal behavior in
vertebrates (Zala and Penn 2004). EDCs can have adverse effects on a range of behaviors
that are controlled by hormones, including reproductive and sexual behavior, activity
level, aggression, communication and motivation (Zala and Penn 2004). It is therefore
likely that analyzing changes in behavior patterns could be used as an indicator, or
biomarker, for detecting harmful environmental contaminants (Zala and Penn 2004). It
has been suggested that behavior might be a more useful indicator or “biomarker” than
standard assays. Behavioral assays are non-invasive, inexpensive and potentially more
powerful than other methods, since behavior is the outcome of many complex
developmental and physiological processes (Zala and Penn 2004). On the other hand,
behavior can be difficult to measure and highly variable. The combination of behavioral
and physiological data could provide a comprehensive method for characterizing the
octopus stress response.
Gene expression patterns are reflective of the timing of particular events in
development. Many developmental genes are highly conserved in the animal kingdom
(Ingham and McMahon 2001). Two important genes are those that code for
orthodenticle-like protein and hedgehog, both of which play critical roles in body
patterning and morphogenesis. Analysis of gene expression changes can provide insight
into the physiological state of an organism. For example, gene expression “rhythms” in
rocky intertidal mollusks allow them to adapt to low-tide heat stress events (Gracey et al.
2008). Since developing larvae are particularly vulnerable to temperature stress, changes
in gene expression could be dramatic and interesting.
The overall goal of this project is to develop techniques to characterize the stress
response of octopus species (O. rubescens and E. dofleini) using epidermal mucus and
developmental gene expression patterns. Information is lacking on stress response in
octopuses and more importantly, non-lethal, non-invasive means to detect it.
Understanding the physiological response of octopuses to stress could be valuable for
conservation purposes, predicting effects of environmental stress on local food chains,
and simply gaining a better understanding of the lives of these popular, local species. It
would be highly useful to isolate biological markers from epidermal surfaces rather than
internal body tissues. A method such as this would allow the animal to live, as well as
save time and cost of sampling. Potential behavioral and molecular stress biomarkers will
be identified in adults using these non-invasive methods, and the gene expression patterns
of two important developmental genes will be analyzed in larvae. Ultimately, this study
will serve to establish a baseline physiological data set for both adult and larval Red
Octopuses
Methods
Epidermal mucus collection
Epidermal mucus was collected from a female Red Octopus (O. rubescens). Three
approaches were attempted to determine the most effective sampling procedure. The first
approach was to collect mucus using a plastic transfer pipet with the octopus still
submerged in the water. The second was to remove the octopus from the water and place
it into a sampling container. The third approach was to remove the liquid left in the
bottom of the sampling container after the octopus was removed. This liquid theoretically
contained a mixture of seawater and mucus.
Protein analysis
Samples were combined with SDS, heated to 100 degrees Celsius for 10 minutes, and run
on an SDS PAGE gel (Pierce 4-20% Tris-Hepes) for 45 minutes at 150 Volts. Gels were
stained with Coomassie Blue Stain for approximately one hour. It was determined that
silver staining was more sensitive to the detection of protein bands, and this procedure
was used for later staining procedures. Non-invasive techniques were used to identify
possible protein biomarkers of stress. Proteins were identified using two approaches.
Discovery-based approach: Mass spectroscopy
Prominent bands were excised from a gel containing samples collected using each of the
three techniques attempted. Bands were chosen based on intensity, pattern and whether or
not they were present in all samples. The excised bands were de-stained according to
Invitrogen protocol. Trypsin digestion was performed according to the Goodlett lab
protocol. The digested proteins were sequenced using mass spectroscopy, and a list of
proteins and short sequences found in the bands was received. Stress or immune-related
proteins were noted, and investigated to determine possible use as biomarkers of stress.
Lanes: 1 2 3 4 5 6 7 8
Figure 1. Protein gel of epidermal mucus samples collected using various sampling
techniques. Lanes 2,3, 7 and 8 contain a 1:1 ratio of mucus collected from the sampling
container and 2X SDS. Lane 4 contains mucus collected underwater. Lanes 5 and 6
contain mucus collected with octopus in the sampling container.
Targeted approach: Western blotting
Heat shock protein 70 (HSP 70) was targeted using the Western blot technique. It was
determined that mucus samples contained protein concentrations too low for the HSP 70
antibodies to detect. Leg tissue samples were collected weekly from this point on. Protein
was extracted from the leg tissue using 500 uL of Cell Lytic. A Bradford protein assay
was performed in order to determine the protein concentration of the extracted samples.
A total of seven leg tissue protein samples containing 9.7 ug of protein were run on an
SDS PAGE gel for 45 minutes at 150 Volts. A Western blot was done using an
Invitrogen Western Breeze (anti-mouse) kit and the anti-HSP 70 antibody. The Western
was then developed according to the Western Breeze protocol.
Behavioral assessment
A web-cam was installed outside of the octopus aquarium. This provided a 24
hour video feed of its activity. Time lapse videos were available online. The octopus’
behavior at randomly determined time intervals was categorized by certain activities
characteristic of varying levels of behavior. These included swimming, crawling, and
remaining stationary on the side of the aquarium. Prior to imposing environmental stress,
baseline behavior was categorized. An online viewer survey was associated with the live
video feed. Viewers were able to check boxes corresponding to these same activity
categories, the results of which were imported into an Excel spreadsheet for later
analysis.
Larval gene expression
Egg samples were collected weekly. RNA was extracted using the Tri-Reagent
isolation protocol. A Bradford nucleic acid assay was performed in order to determine the
RNA concentration of the samples. cDNA was made by reverse transcription. Primers for
two developmental genes were designed, orthodenticle-like protein (OTX, Octopus
bimaculoides) and hedgehog (HH, Octopus bimaculoides). Real-Time PCR was done
using an Opticon system. Data was analyzed according to Miner.
Results
Success varied in relation to the sampling technique used. The underwater
sampling method resulted in mucus samples that were too dilute with seawater to produce
bands after gel electrophoresis (Figure 2). Samples collected from the sampling container
had sufficient protein concentrations to produce easily visible bands. Mucus pipetted
directly from the epidermal surface produced bands similar in intensity and pattern to the
samples collected from the sampling container.
Lanes: 1 2 3 4 5 6 7
Figure 2. Mucus samples collected using three sampling techniques were visualized using
gel electrophoresis. Lanes 2,3, 6 and 7 contain mucus collected from the sampling
container. Lane 4 contains mucus collected underwater. Lane 5 contains mucus collected
with the octopus removed from the water.
Identification of protein biomarkers
Discovery-based approach
Proteins present in the excised bands were identified using mass spectroscopy.
Table 1. Representative mass spectroscopy results after trypsin digestion. See appendix for
complete list of mass spectroscopy results.
Protein Total number of peptides
Description Peptide sequence
CAS1_BOVIN 20 (P02662) Alpha-S1-casein precursor
YLGYLEQ
LACB_BOVIN 3 (P02754) Beta-lactoglobulin precursor
VLVLDTDYK
ACT_HYDAT,ACTC_STYPL 2 (Q00215) Actin, cytoplasmic
GYSFTTTAER
CASB_BOVIN 25 (P02666) Beta-casein precursor
DM[147]PIQAF
STAT_HUMAN 14 (P02808) Statherin precursor
FGYGYGPYQPVPEQPLYPQPYQPQYQQYTF
VIME_HUMAN,VIME_PANTR 111 (P08670) Vimentin
ILLAELEQLK
PALA_EMENI 2 (P79020) pH-response regulator protein
DDISSALVR
DNAK_BLOFL 1 (Q7VQL4) Chaperone protein dnaK (Heat shock protein 70)
HSQVFSTAEDNQSAVTIHVLQGER
These lists of proteins were sorted through and condensed into a short list of
proteins possibly related to stress and immune function. They were thus assumed to be
potentially useful as biomarkers of stress (Lahov and Regelson 1996, Barak et al. 2005).
Table 2. Selected proteins identified from epidermal mucus samples by mass spectroscopy
with functions related to stress or immune function. These proteins have potential use as
biomarkers.
Protein FunctionCasein Antioxidant peptide, radical scavenging
activity, inhibits growth of E. coliHeat Shock Protein 70 (Chaperone protein dnaK) Chaperone and monitor for other proteins,
maintains conformations, disposal of degraded proteins
Dermcidin Antimicrobial, limits skin infection by potential pathogens
Targeted protein analysis
The antibody for Heat Shock Protein identified the presence of the protein in the
extracted leg tissue samples (Figure 3).
Lanes: 1 2 3 4 5 6 7 8 9 10 11 12
Figure 3. Nitrocellulose membrane following Western blotting. The dark marker
indicates the presence of HSP 70 in the leg tissue samples. Lanes 2 through 8 contain 9.7
ug of leg tissue protein, loaded into wells in chronological order. The lane 2 sample was
collected on 10/24/2008, the lane 8 sample was collected on 4/1/2009. Lanes 9 through
12 contain 20 ul of mucus collected from the skin with the octopus removed from the
water. The lane 9 sample was collected on 1/28/2009 and the lane 12 sample was
collected on 4/8/2009.
Heat shock protein is known to be produced in increased amounts during stressful
conditions. Therefore, HSP 70 could be a useful biomarker for identifying stress in
octopus species.
Identification of behavior biomarkers
Crawling
Swimming
On Side of Aquarium
Figure 4. Baseline activity patterns were established after time lapse video analysis.
Prior to experimentation, behavior patterns were categorized. The octopus was
quite active. At the three randomly determined time intervals, it was often crawling and
swimming in the aquarium. 40% of time was spent crawling on the substrate or side of
aquarium, 40% of time was spent swimming, and a minimal amount of time (20%) was
spent stationary on the side of the aquarium (Figure 3). These patterns will serve as a
baseline level of activity (control) to be used for comparison after stressful conditions are
imposed.
CrawlingBroodingOn Side of AquariumNo Data
Figure 5. The activities of the octopus were categorized after eggs were laid.
After the eggs were laid, behavior was again categorized to determine the impact
of post-reproductive senescence (a biological rather than environmental stressor) on
behavior. The general behavioral pattern showed a shift from active crawling and
swimming to stationary activities. Immediately after the eggs were laid, the female
octopus began a constant routine of brooding. Brooding entailed positioning itself on top
of the eggs and blowing water through the siphon to oxygenate the egg strands.
Approximately 90% of time was spent brooding the eggs on the side of the aquarium,
while 2% of time was spent crawling. For 8% of the time, data was not available due to
camera malfunction (Figure 4).
Larval gene expression
1
10
100
1000
10000
100000
1000000
1/28/092/4/09
2/11/09
2/18/09
2/25/093/4/09
3/11/09
3/18/09
3/25/094/1/09
4/8/09
Date
Exp
ressio
n (
Fold
over
Min
imu
m)
Figure 6. Orthodenticle-like protein expression (log of fold over minimum) in octopus
eggs collected weekly from 1/28/09 to 4/12/09.
There was a 100,000-fold increase in expression of the gene for orthodenticle-like
protein (OTX) over the course of the 10 week sampling period. There was zero gene
expression on 1/28/09, which was the day the eggs were laid. A minimum expression
(Plotted as zero in Figure 5) was quantified on 2/4/09. From 2/4/09 to 4/12/09, the
expression of OTX increased fairly steadily up to its maximum value of 100,000 fold
over minimum.
1
10
100
1000
1/28/092/4/09
2/11/09
2/18/09
2/25/093/4/09
3/11/09
3/18/09
3/25/094/1/09
4/8/09
Date
Exp
ressio
n (
Fold
over
Min
imu
m)
Figure 7. Hedgehog expression (log of fold over minimum) in octopus eggs collected
weekly from 1/28/09 to 4/12/09.
The hedgehog gene was expressed relatively late in development. A minimum
expression was quantified on 3/25/09, with zero expression up until that date. Maximum
expression was reached on 4/8/09, which represents an approximate 300-fold increase
over minimum over the course of several weeks. Expression declined after 4/8/09, and
reached a final value of less than a 100-fold increase over minimum at the end of the
sampling period.
Discussion
The development of non-invasive sampling techniques was fairly successful. 3
methods were tested, and results varied. It was determined that collecting epidermal
mucus from the sampling container, and directly from the epidermal surface with the
octopus removed from the water were the two most useful methods. In this sense,
usefulness was measured by the intensity and number of protein bands present after
protein gel electrophoresis. Mucus samples collected underwater were not useful, as no
bands were visible. Therefore, it is likely that collecting mucus from the skin and from
the sampling container could be useful techniques as a first step to identifying protein
biomarkers. Both of these methods were minimally invasive. Stress was imposed on the
octopus during both procedures, as the animal was removed from the water and was
exposed to air for approximately 5 minutes. This air exposure could also introduce
thermal stress, as the temperature of the air was approximately 10 degrees higher than the
temperature of the aquarium water. Therefore, it is possible that stress-related proteins
could be present in the control samples. Differences in the expression of many proteins
will have to be measured, rather than simply noting the presence of one or two stress-
related proteins in the experimental samples.
The non-invasive methods developed were used prior to identification of proteins.
The discovery-based approach provided an extensive list of proteins after mass
spectroscopy sequencing. Several interesting stress and immune related proteins were
present, and further investigation into their functions identified them as possible
biomarkers. Alpha, beta, and kappa caseins composed a large percentage of the proteins
identified. Caseins are milk proteins that function as antioxidants. Short casein peptides
participate in various biological activities. Some function as immunomodulators
(immunostimulators in cows and humans) (Fiat and Jolles 1988). Others have radical
scavenging activity (Clausen et al. 2009) and have been found to inhibit the growth of
E.coli, staphylococcus, and streptococcus bacteria (Lahov and Regelson 1996). It is
possible that caseins with similar functions could be found in octopus species. Exposure
to bacterial pathogens would certainly result in casein production. It is possible that
thermal or chemical stress could induce the production of casein proteins as part of a
stress response.
Another interesting protein with similar function is dermcidin. Dermcidins are
potent antimicrobial proteins that defend against pathogenic microorganisms including S.
aureus and E. coli (Barak et al. 2005). It is likely that dermcidin production would
increase when faced with a pathogenic stressor, and possible that thermal or chemical
stress could induce a response.
Heat shock protein 70 was detected in epidermal mucus samples. Heat shock
proteins are the most conserved proteins in both prokaryotes and eukaryotes (Schmitt et
al. 2007). They accumulate in cells exposed to thermal or other stressful stimuli. They
function as molecular chaperones and help cells to survive potentially lethal conditions,
as well as regulate apoptosis (Didelot et al. 2006). Heat shock proteins assist other
proteins in maintaining correct conformations during environmental stress, and transport
degraded proteins to proteasomes for disposal (Schmitt et al. 2007). Because heat shock
protein 70 is highly conserved and directly related to stress response, it was suitable for a
targeted-protein analysis using the Western blot technique. HSP 70 was detected by its
antibody in protein extracted from octopus leg tissue under the control sampling
conditions. It is potentially the most useful protein biomarker identified, as its function is
well-known and applicable to an experiment in which thermal stress is imposed.
However, the sampling technique required to perform a Western blot was more invasive
than the collection of epidermal mucus for mass spectroscopy. A Western blot was
attempted using epidermal mucus, but it was determined that the protein concentrations
of the samples were too low to get a clear result. It is also possible that HSP 70 is not
found in mucus. Small leg tissue samples were collected, which seemed to have little
effect on the well-being of the octopus. Its activity level remained high after the
procedure. Octopus leg tissue regenerates after damage, and after several days the leg
began to re-grow. As this procedure did not require anesthesia and did not cause long-
term damage to the octopus, it is still considered to be minimally invasive.
The techniques developed to analyze and categorize octopus behavior provided a
general, baseline pattern of daily activity. The difference between the activity patterns
before and after egg-laying was dramatic. The most obvious change was a shift from
active swimming and crawling to near constant brooding. The shift is a clear indicator of
the level of parental care provided by female octopuses to their young. The technique of
categorizing behavior based on time-lapse videos at randomly determined intervals could
be useful in evaluating the effect of environmental stress on octopus physiology.
Behavior is a direct result of physiological condition (Zala and Penn 2004). Behavioral
analysis is practical for many reasons. It is inexpensive, comprehensive and most
importantly for this study, non-invasive.
Future work would incorporate a controlled experiment to test whether the
production of casein, dermcidin, and heat shock protein 70 differs between control (non-
stressed) and experimental (stressed) conditions. The baseline physiological data could be
used for comparison purposes. This experiment would also validate the effectiveness of
the non-invasive sampling techniques developed.
The analysis of gene expression in octopus paralarval development revealed interesting
patterns. The expression patterns of the two genes investigated, orthodenticle-like protein
(OTX) and hedgehog (hh), varied greatly over time.
Orthodenticle-like protein is a DNA binding protein with the essential function of
regulating head and central nervous system development (Klein and Li 2002). OTX
proteins are widespread throughout the animal kingdom, and have evolved specialized
roles in some taxonomic groups. OTX appears to be expressed early in O. rubescens
development. This could indicate that morphogenesis of the anterior neural structures of
octopuses occurs close to the onset of development.
The hedgehog gene family has been found in vertebrates as well as several
invertebrate taxa, including mollusks. Hedgehog is expressed in both embryonic and
adult tissues, where it mediates development, growth, patterning and morphogenesis
(Grimaldi et al. 2007). Several studies have shown that hedgehog genes are highly
conserved in invertebrates (Ingham and McMahon 2001). Grimaldi et al. (2007) showed
that the hedgehog pathway is involved in the differentiation of striated muscle fibers in
the cuttlefish (Sepia officinalis) mantle. It is possible that hedgehog could also be
involved in muscle differentiation of octopus, since cuttlefish and octopuses are in the
same phylum. Hedgehog is expressed later in development (relative to OTX), which
could indicate that it is involved with patterning and morphogenesis at later stages of
development. This could be the time frame in which muscle fiber development occurs.
However, it is possible that hedgehog was expressed at low levels throughout
development, but the concentration was too low to be detected by the Real-Time PCR
equipment.
Further investigation is necessary to determine the exact roles of orthodenticle-
like protein and hedgehog in octopus larval development. General expression patterns
were identified, including timing during development and relative increase in expression
over time. These increases in expression are likely due to a specific developmental event,
such as brain morphogenesis in the case of orthodenticle-like protein, or muscle fiber
differentiation in the case of hedgehog. These data could be used for comparison
purposes, possibly to identify changes in gene expression due to particular stressors, such
as temperature. Future work would involve mapping gene expression in specific body
regions and at specific times to determine the correlation between expression and the
development of organs.
The overall goal of this project was to determine if the stress-response of adult
octopuses can be characterized using non-invasive methods. This limited the scope of
possible techniques. A genetic analysis would have required tissue or hemolymph
samples which are more difficult to obtain, and involve procedures that are often harmful
to the animal. For this reason, institutions such as aquariums may value non-invasive
methods over hemolymph or tissue collection. Collecting epidermal mucus was fast,
inexpensive, and relatively harmless. The techniques used provided valuable information
about the protein composition of mucus, and sequencing identified several proteins that
may be related to stress-response. Identifying a stressed physiological state in a particular
animal could allow aquariums to ensure that the conditions of their exhibits do not
negatively affect the animals. Since senescence is a time period characterized by high
levels of stress and physiological change, these non-invasive methods could allow
researchers and aquarists to predict the onset of senescence, and therefore reproduction
and subsequent death.
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Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
YLGYLEQ 1
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
EPMIGVNQELAYFYPELFR
2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
EPM[147]IGVNQELAYFYPELFR
2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
FFVAPFPEVFGK 2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
HQGLPQEVLNENLLR 2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
IGVNQELAYFYPELFR 2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
YLGYLEQLLR 2
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
EPMIGVNQELAYFYPELFR
3
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
EPM[147]IGVNQELAYFYPELFR
3
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
HQGLPQEVLNENLLR 3
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha- HQGLPQEVLNEN 2
Appendix
S1-casein precursor
1 CAS1_BOVIN 1 26.2 12 20 3.53 (P02662) Alpha-S1-casein precursor
EVLNENLLR 2
1 CAS2_BOVIN 1 23.4 5 6 1.06 (P02663) Alpha-S2-casein precursor [Contains: Casocidin-1 (Casocidin-I)]
NAVPITPTL 1
1 CAS2_BOVIN 1 23.4 5 6 1.06 (P02663) Alpha-S2-casein precursor [Contains: Casocidin-1 (Casocidin-I)]
ALNEINQFYQK 2
1 CAS2_BOVIN 1 23.4 5 6 1.06 (P02663) Alpha-S2-casein precursor [Contains: Casocidin-1 (Casocidin-I)]
FPQYLQYLYQGPIVLNPWDQVK
3
1 CAS2_BOVIN 1 23.4 5 6 1.06 (P02663) Alpha-S2-casein precursor [Contains: Casocidin-1 (Casocidin-I)]
FALPQYLK 2
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 CAS2_BOVIN 1 23.4 5 6 1.06 (P02663) Alpha-S2-casein precursor
PITPTLNR 1
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
YPVEPFTESQ 1
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
DMPIQAFLLYQEPVLGPVR
2
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor DM[147]
PIQAFLLYQEPVLGPVR 2
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
FQSEEQQQTEDELQDK 2
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
LLYQEPVLGPVR 2
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
DMPIQAFLLYQEPVLGPVR
3
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor DM[147]
PIQAFLLYQEPVLGPVR 3
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
IHPFAQTQSLVYPFPGPIPN
2
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
PIQAFLLYQEPVLGPVR 2
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta- YPVEPFTESQ 2
casein precursor1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-
casein precursorIHPFAQTQSLVYPFPGPIPN
3
1 CASB_BOVIN 1 29 12 19 3.29 (P02666) Beta-casein precursor
DM[147]PIQAF 1
1 LACB_BOVIN,LACB_BUBBU
1 16.3 3 4 0.68 (P02754) Beta-lactoglobulin precursor (Beta-LG) (Allergen Bos d 5),(P02755) Beta-lactoglobulin precursor (Beta-LG)
VLVLDTDYK 2
1 LACB_BOVIN,LACB_BUBBU
1 16.3 3 4 0.68 (P02754) Beta-lactoglobulin precursor (Beta-LG) (Allergen Bos d 5),(P02755) Beta-lactoglobulin precursor (Beta-LG)
VYVEELKPTPEGDLEILLQK
3
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 LACB_BOVIN,LACB_BUBBU
1 16.3 3 4 0.68 (P02754) Beta-lactoglobulin precursor (Beta-LG) (Allergen Bos d 5),(P02755) Beta-lactoglobulin precursor (Beta-LG)
VLDTDYK 1
1 STAT_HUMAN
1 54.8 5 14 2.42 (P02808) Statherin precursor
FGYGYGPYQPVPEQPLYPQPYQPQYQQYTF
3
1 STAT_HUMAN
1 54.8 5 14 2.42 (P02808) Statherin precursor
IGRFGYGYGPYQPVPEQPLYPQPYQPQYQQYTF
3
1 STAT_HUMAN
1 54.8 5 14 2.42 (P02808) Statherin precursor
RIGRFGYGYGPYQPVPEQPLYPQPYQPQYQQYTF
3
1 TRY1_RAT 1 8.1 2 3 0.51 (P00762) Anionic trypsin-1 precursor (EC 3.4.21.4) (Anionic trypsin I) (Pretrypsinogen I)
LGEHNINVLEGDEQFINAAK
2
1 TRY1_RAT 1 8.1 2 3 0.51 (P00762) Anionic trypsin-1 precursor (EC 3.4.21.4) (Anionic trypsin I) (Pretrypsinogen I)
LGEHNINVLEGDEQFINAAK
3
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 TRY2_CANFA
1 10.1 2 4 0.69 (P06872) Anionic trypsin precursor (EC 3.4.21.4)
DNDIMLIK 1
1 TRY2_CANFA
1 10.1 2 4 0.69 (P06872) Anionic trypsin precursor (EC 3.4.21.4)
LGEYNIDVLEGNEQFIN 2
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
DNDIMLIK 1
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
EGNEQFINAAK 1
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
LGEHNIDVLEGN 1
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
LGEHNIDVLEGNEQ 1
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
FNGNTLDNDIMLIK 2
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
FNGNTLDNDIM[147]LIK
2
1 TRYP_PIG 1 34.6 45 249 40.49 (P00761) Trypsin precursor (EC 3.4.21.4)
LGEHNIDVLEGNEQFINAAK
2
Group Probability
Protein Protein Probability
Percent Coverage
Number of Unique Peptides
Total Number of Peptides
Percent Share of Spectrum ID’s
Description Peptide Sequence Precursor Ion Charge
1 VIME_HUMAN,VIME_PANTR
1 17.8 8 111 18.91 (P08670) Vimentin,(Q5R1W8) Vimentin
ILLAELEQLK 2
1 VIME_HUMAN,VIME_PANTR
1 17.8 8 111 18.91 (P08670) Vimentin,(Q5R1W8) Vimentin
LLQDSVDFSLADAINTE 2
1 VIME_HUMAN,VIME_PANTR
1 17.8 8 111 18.91 (P08670) Vimentin,(Q5R1W8) Vimentin
LLQDSVDFSLADAINTEFK
2
1 VIME_HUMAN,VIME_PANTR
1 17.8 8 111 18.91 (P08670) Vimentin,(Q5R1W8) Vimentin M[147]
ALDIEIATYR 2
1 VIME_HUMAN,VIME_PANTR
1 17.8 8 111 18.91 (P08670) Vimentin,(Q5R1W8) Vimentin
SSVPGVRLLQDSVDFSLADAINTE
2