key: cord-0288939-14wnmr8q
authors: Neely, Benjamin A.; Janech, Michael G.; Fenton, M. Brock; Simmons, Nancy B.; Bland, Alison M.; Becker, Daniel J.
title: Surveying the vampire bat (Desmodus rotundus) serum proteome: a resource for identifying immunological proteins and detecting pathogens
date: 2020-12-04
journal: bioRxiv
DOI: 10.1101/2020.12.04.411660
sha: b558fb71e37fdc179bfa9ea216775d7a7d4370ef
doc_id: 288939
cord_uid: 14wnmr8q

Bats are increasingly studied as model systems for longevity and as natural hosts for some virulent viruses. Yet our ability to characterize immune mechanisms of viral tolerance and to quantify infection dynamics in wild bats is often limited by small sample volumes and few species-specific reagents. Here, we demonstrate how proteomics can overcome these limitations by using data-independent acquisition-based shotgun proteomics to survey the serum proteome of 17 vampire bats (Desmodus rotundus) from Belize. Using just 2 μL of sample and relatively short separations of undepleted serum digests, we identified 361 proteins across five orders of magnitude. Data are available via ProteomeXchange with identifier PXD022885. Levels of immunological proteins in vampire bat serum were then compared to human plasma via published databases. Of particular interest were anti-viral and anti-bacterial components, circulating 20S proteasome complex, and proteins involved in redox activity; whether any results are specific to vampire bats could be assessed by future pan-mammalian analyses. Lastly, we used known virus proteomes to identify Rh186 from Macacine herpesvirus 3 and ORF1a from Middle East respiratory syndrome-related coronavirus, indicating that mass spectrometry-based techniques show promise for pathogen detection. Overall, these results can be used to design targeted mass-spectrometry assays to quantify immunological markers and detect pathogens. More broadly, our findings also highlight the application of proteomics in advancing wildlife immunology and pathogen surveillance.

Bats are a hyper-diverse and geographically widespread order (Chiroptera), accounting for over 20 % of all mammal species 1 . Owing to their capacity for flight and wide range of trophic habits (e.g., frugivory, nectarivory, insectivory, carnivory, sanguivory), bats provide critical ecosystem services that include seed dispersal, pollination, and predation of insects 2 . Unique features of bats among mammals, such as the capacity for powered flight and long lifespans despite small body sizes, also make this order interesting for basic research in ecology and evolution 3, 4 .

Recently, bats have also become model systems for studies of the microbiome and sociality 5, 6 .

However, because some bats are common in anthropogenic landscapes, they are increasingly studied for their ability to harbor pathogens with high virulence in humans and domestic animals 7, 8 . In particular, bats carry more zoonotic viruses than most other mammalian orders 9 , and they are the confirmed reservoir hosts for Hendra virus, Nipah virus, Marburg virus, an array of lyssaviruses (e.g., rabies virus), and SARS-like coronaviruses [10] [11] [12] [13] . Spillovers of these sometimes lethal viruses, from bats to humans, are often driven by ecological changes that alter infectious disease dynamics in wild bat populations and change interactions between bats and recipient hosts 14, 15 . However, with some exceptions (e.g., lyssaviruses), these viruses may not typically cause clinical disease in bats 16 . Although the high richness of zoonotic viruses in bats may simply be a function of their vast species diversity 17 , tolerance to virulent viruses is likely driven by distinct aspects of immunity in these flying mammals, including robust complement, constitutive expression of type I interferons (e.g., IFN-α), and high combinatorial diversity in immunoglobulin genes 4, [18] [19] [20] . Accordingly, contemporary studies of zoonotic pathogens in bats have focused on characterizing immunological factors that facilitate tolerance or shedding of viruses, quantifying viral diversity, and identifying spatial and temporal pulses of infection [21] [22] [23] .

Traditionally, efforts to assess the immunological state of wild bats and detect viruses have relied on relatively simple tools. Most bat species are sufficiently small that only modest volumes of blood can be safely collected under non-lethal procedures 24 ; 74% of bat species weigh less than 30 grams as adults 25 . Small blood volumes and lack of species-specific reagents for bats generally restrict the scope of possible immune assays 26, 27 . Remote field sites also pose significant challenges for sample storage and transport at ideal temperatures. Despite these obstacles, techniques such as in vitro microbial killing assays, enzyme-linked immunosorbent assays, and in vivo antigen challenge have helped to broadly characterize complement, antibody, and cellular immune response in wild bats and how these phenotypes vary with life history (e.g., reproduction) and environmental conditions [28] [29] [30] . Similarly, polymerase chain reaction (PCR) has formed the primary basis of virus detection 31 . However, because bat colonies can be large (e.g., hundreds to over 20 million individuals 32 ) and prevalence of active viral infection is generally low, serology and the detection of virus-specific antibodies has also commonly been employed 33 . Although serological surveys have been important for characterizing virus circulation in bats, antibody cross-reactivity and inconsistent cut-off thresholds can limit their interpretability 34 .

Given these restrictions, studies of bat immunology and virology have increasingly benefitted from modern bioanalytical approaches. Researchers employing global profiling techniques, such as RNA-Seq-based transcriptomics, have begun to contribute new resources for bat immunology and to illuminate the broad immune response of bats to viral infections 35, 36 .

Similarly, metagenomic approaches have helped reduce bias in broad characterization of bat viral diversity 37, 38 . In addition to these approaches, proteomics can provide a complementary modality to define the molecular landscape. Proteomics is uniquely useful when applied to blood, because the blood proteome is mostly secreted from organs such as the liver 39 , thereby permitting interrogation of the circulating protein phenotype beyond cellular transcript profiling.

Using the relatively small sample volumes that typify bat field studies (e.g., < 10 μL), proteomic analysis of blood can identify and relatively-quantify hundreds of proteins, including but not limited to those involved in host response to infection and other useful immunological biomarkers 40 . Prior applications of serum proteomics in bats have described proteins involved in shifts in innate immunity and blood coagulation between hibernating and active greater mouseeared bats (Myotis myotis) 41 as well as between North American and European Myotis species that vary in infection with Pseudogymnoascus destructans, which causes white-nose syndrome 42 . Proteomic applications to other bat tissues, such as saliva, brain, and lung, have identified possible immunomodulatory properties in vampire bats (Desmodus rotundus) 43 , neuronal differences between active and torpid horseshoe bats (Rhinolophus ferrumequinum) 44 , and upregulation of cell-mediated immunity in flying foxes (Pteropus alecto) compared with ferrets infected with Hendra virus 45 . Given the general utility of proteomic analysis, we expected a survey of the vampire bat serum proteome should provide complementary information to existing approaches, while also providing a more complete survey of the underlying molecular landscape.

Here, we used data-independent acquisition-based shotgun proteomics (i.e., bottom-up proteomics) to profile the undepleted serum proteome of 17 bats from two locations. We focused this work on vampire bats, a species that has an obligate diet of blood and feeds on prey as diverse as sea lions, tapirs, livestock, and humans [46] [47] [48] , providing vast opportunities for transmission of viruses (e.g., rabies virus, adenovirus, herpesvirus) to and from these prey 49-51 . Our results demonstrate the feasibility and capabilities of serum proteomic analyses in wild bats, including possibilities to simultaneously detect immunological components and viruses as well as to establish preliminary ranges of vampire bat proteins for comparison with other mammals. Vampire bats were captured with mist nets and harp traps set along trails and adjacent to known roost sites. All individuals were issued a unique incoloy wing band (3.5 mm, Porzana

Inc.) and identified by sex, age, and reproductive status 63 . Serum was obtained by lancing the propatagial vein with a 23-gauge needle to collect blood and centrifuging resulting samples in serum separator tubes followed by short-term freezing at -20 °C until long-term -80 °C storage.

Bleeding was stopped with styptic gel, and all bats were released at their capture location. Field protocols followed guidelines for safe and humane handling of bats issued by the American Society of Mammalogists 24 and were approved by the University of Georgia Animal Care and Use Committee (A2014 04-016-Y3-A5). Bat sampling was authorized by the Belize Forest Department under permit number CD/60/3/15 (21) . Specimen use for proteomic analysis was approved by the NIST Animal Care and Use Coordinator (NIST ACUC) under approval MML-AR19-0018. We included 17 serum samples for proteomic analysis, from 11 bats sampled at LAR (10 males, one female) and six bats sampled at KK (five males, one female). This information and the experimental key can be found in Supplemental Table S1 .

Prior to analysis, the sample set was randomized and assigned an experimental key to avoid bias and minimize batch effects. The 17 serum samples were thawed then centrifuged at 13 000 x gn for 8 min at 4 °C. The S-Trap method was used for digestion with the S-Trap micro column (ProtiFi; ≤ 100 μg binding capacity), and the specific method is described below. Based on prior work with other mammalian sera, we assumed a protein concentration of approximately 50 μg/μL (this value can vary but assuming at least 50 μg/μLwas used for estimating enzyme for the digest). Therefore, 2 μL (approximately 100 μg protein) of each sample was mixed with 48 μL 

Peptide mixtures in 0.1% formic acid (volume fraction) were analyzed using an UltiMate 3000

Nano LC coupled to a Fusion Lumos Orbitrap mass spectrometer (Thermo Fisher Scientific).

Using the original sample randomization yielded a randomized sample order and injection volumes were determined for 0.5 μg loading (between 0.37 and 0.95 μL sample). One sample from bat D141 (experimental key Bat_20) was used as a technical replicate to evaluate technical variability across the run (Supplemental Figure S1 ), while the two aforementioned human serum pools were analyzed in the same manner as the bat sera. Peptide mixtures were loaded onto a PepMap 100 C18 trap column (75 µm id x 2 cm length; Thermo Fisher Scientific) at 3 µL/min for 10 min with 2 % acetonitrile (volume fraction) and 0.05 % trifluoroacetic acid (volume fraction) followed by separation on an Acclaim PepMap RSLC 2 µm C18 column (75µm id x 25 cm length; Thermo Fisher Scientific) at 40 °C. Peptides were separated along a 60 min two-step gradient of 5 % to 30 % mobile phase B (80 % acetonitrile volume fraction, 0.08 % formic acid volume fraction) over 50 min followed by a ramp to 45 % mobile phase B over 10 min and lastly ramped to 95% mobile phase B over 5 min, and held at 95 % mobile phase B for 5 min, all at a flow rate of 300 nL/min.

The Fusion Lumos was operated in positive polarity with a data-independent acquisition (DIA) method constructed using the targetedMS2 module (as opposed to the built-in DIA module). The full scan resolution using the orbitrap was set at 120 000, the mass range was 399 to 1200 m/z (corresponding to the DIA windows used), 30 % RF lens was set, the full scan ion target value was 4.0e5 allowing a maximum injection time of 20 ms. A default charge of 4 was set under MS Global Settings. As stated, DIA windows were constructed using the targetedMS2 module. Each window used higher-energy collisional dissociation (HCD) at a normalized collision energy of 32 with quadrupole isolation width at 21 m/z. The fragment scan resolution using the orbitrap was set at 30 000, the scan range was specified as 200 to 2000 m/z, ion target value of 1.0e6 and 60 ms maximum injection time. Data were collected as profile data in both MS1 and MS2, though the authors wish to note that using centroid data is possible for most DIA software. The DIA window scheme was an overlapping static window strategy such that each of the 40 windows were 21 m/z wide, with 1 m/z overlap on each side covering the range of 399 to 1200 m/z. The window centers were specified in the mass list table (with z = 2), such that they were 409.5, 429.5, 449.5, ..., 1189.5. The method file (85min_DIA_40x21mz.meth) is also included in the PRIDE submission. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE 64 partner repository with the dataset identifier PXD022885.

Analysis was performed using Spectronaut (v13. 6.190905 .43655). The following settings were used. Sequences: Trypsin selected, max pep length 52, min pep length 7, two missed cleavages, KR as special amino acids in decoy generation, toggle N-terminal M set to true. Labelling: no labelling settings were used. Applied modifications: maximum of five variable modifications using fixed carbamidomethyl (C), and variable acetyl (protein N-term) and oxidation (M).

Identification: per run machine learning, Q-value cut-off of 0.01 for precursors and proteins, single hits defined by stripped sequence, and do not exclude single hit proteins, PTM localization set to true with a probability cut-off of 0.75, kernel density p-value estimator. Quantification:

interference correction was used with excluding all multi-channel interferences with minimum of 2 and 3 for MS1 and MS2, respectively, proteotypicity filter set to none, major protein grouping by protein group ID, minor peptide grouping by stripped sequence, major group quantity set to mean peptide quantity, a Major Group Top N was used (min of 1, max of 3), minor group quantity set to mean precursor quantity, a Minor Group Top N was used (min1, max of 3), quantity MS-level used MS2 area, data filtering by q-value, cross run normalization was used with global median normalization and automatic row selection, no modifications or amino acids were specified, best N fragments per peptide was set to between 3 and 6, with ion charge and type not used. Workflow: no workflow was used. Post Analysis: no calculated explained TIC or sample correlation matrix, differential abundance grouping using major group (from quantification settings) and smallest quantitative unit defined by precursor ion (from quantification settings), differential abundance was not used for conclusions. The fasta file used Table S2 ). These identifications were converted to human orthologs to aid in downstream analysis and for comparison to other studies. This was accomplished by using a series of python scripts (Anaconda v2019.07; conda v4.7.11; Python v3.6.8) from Github on the following two repositories: pwilmart/PAW_BLAST and pwilmart/annotations, retrieved November 18, 2019. Broadly, these tools take a list of identifiers to create a subset fasta (make_subset_DB_from_list_3.py), which is then searched against a human fasta (db_to_db_blaster.py) using a local installation of BLAST+ 2.9.0 65 . The results were further annotated using add_uniprot_annotations.py. The 376 vampire bat proteins were assigned human orthologs, which were then manually inspected for incorrect assignments. Such assignments can happen when a protein is not present in humans (e.g., beta-lactoglobulin 1 or inhibitor of carbonic anhydrase), or if the blast hit disagrees with the original annotation, in which case the original annotation is preserved (e.g., apolipoprotein R was matched to C4bbinding protein alpha chain). Finally, duplicate entries were summed together into a single nonredundant entry. An intermediate table (Supplemental Table S2 ) is given that delineates which entries had manually assigned gene names, or were duplicates to be summed. The resulting table included mapped orthologs with UniProtKB links (Supplemental Table S3 ). Gene ontology (GO) term sorting was performed by using GO search terms in UniProtKB along with the human taxon identifier (9606), yielding a list of human gene symbols that was used to subset the vampire bat results. Specifically in Supplemental Table S3 , the complement activation Gene Ontology (GO) term (GO:0006956) was used to identify 31 bat proteins. In addition to vampire bat proteome, identifications and relative abundances of the control pooled human serum can be found in Supplemental Table S4 , but were not used for comparison.

The serum proteome of the vampire bat was compared to the plasma proteome of the human described on the Human Blood Atlas by using values from Table 1 "Protein detected in human plasma by mass spectrometry" from the Human Blood Atlas website (https://www.proteinatlas.org/humanproteome/blood/proteins+detected+in+ms; accessed 15 June 2020). This table was combined with the relative abundance and resulting ranks of the 361 proteins identified (Supplemental Table S5 ). The rank of the shared 323 proteins was compared by determining the absolute difference in rank divided by the minimum rank, referred to as "Rank Delta". An arbitrary cut-off of 3 was chosen, but the complete list was still manually inspected for proteins of interest. Only proteins that were exceptionally elevated (or closely related to those that were elevated) in the vampire bat serum proteome were considered. Some proteins like PRDX1 (136th in bat and 432 in human) were less than 3 in their rank delta, but were still considered of interest. This final list of proteins of interest can be found in Supplemental Table S6 , along with links to both UniProt and Human Blood Atlas entries.

Studying the interactions between hosts and pathogens is important to understand infectious disease risks, yet such research is hampered by our poor knowledge of the underlying biochemical landscape for most host species. Bats offer a unique opportunity to investigate how immunological components may confer the ability to harbor virulent viruses, a topic of considerable interest particularly in light of the current COVID-19 pandemic. Because complement plays a key role in innate immunity and functions as a bridge between innate and adaptive responses [66] [67] [68] , prior studies have mostly used microbicidal assays using pathogens with complement-dependent killing to profile levels of these proteins in bats, demonstrating individual and environmental sources of variation [28] [29] [30] 69, 70 . We profiled the serum proteome of vampire bats as a first step at broadly describing the bat serum proteome. This inventory allowed investigating not only complement proteins, but also a global investigation of the bat serum proteome, including other components of the innate immune response, as well as detection of viral proteins, and can serve as a resource to develop targeted mass spectrometry-based assays.

Blood is a unique biofluid that is proximal to most organs, containing cells and secreted proteins. The considerable dynamic range of proteins in serum and plasma has been frequently described in humans, spanning at least eight orders of magnitude, though approximately 10 proteins account for 90 % of the plasma proteome 39, 71 . Similarly, we unsurprisingly found the vampire bat serum proteome encompassed a dynamic range of five orders of magnitude ( Figure   1A ). The top four proteins (albumin, immunoglobulin lambda-1 light chain, hemoglobin subunit beta, and alpha-1-antitrypsin) accounted for 50% of the total abundance estimated using DIA.

Ranges for the top 20 proteins (based on average abundance; Figure 1B ) were determined using protein abundance from the 17 individuals. Despite the difficulties in making direct comparisons between the vampire bat serum proteome and that of other mammals, it is possible to specifically evaluate complement components in bat serum. The complement activation Gene Ontology (GO) term (GO:0006956), which includes the lectin pathway, was used to highlight relative levels of 31 proteins in bat serum ( Figure 1C ) and indicate their rank and abundance in the serum proteome ( Figure 1A) . Apolipoprotein R and manose-binding protein A were added since they are not present in humans but are likely involved in complement activation. It would be interesting to infer that these complement protein levels are higher in bats than other mammals, but without adequate reference ranges, and given the technical artifacts of serum preparation across species, these comparisons are currently difficult at best and an avenue for future comparative study. Although blood has been extensively studied in humans, it is surprisingly difficult to compare mass spectrometry-based analysis between human studies, much less between different species. The current study used a pooled human converted plasma sample (Supplemental Table   S4 ) to enable this comparison. Additionally, the Human Blood Atlas 72 was used as a reference (Supplemental Table 5 ), with reported approximate concentrations of over 3000 proteins detected by mass spectrometry in human plasma. For an exploratory analysis, using these two datasets is acceptable, but two key caveats should be acknowledged. First, ranges of human concentrations are needed, which is obscured in a pooled sample as well as in the current Human Blood Atlas. Second, the wild bat samples may have had technical artifacts (e.g., hemolysis), which is evident by the high levels of hemoglobin subunit beta likely resulting from ruptured red blood cells 73 ( Figure 1B) . Ongoing efforts by our group and others will continue to define the serum and plasma proteome in humans and other species, and we expect more population-level data with protein abundance ranges to become available and more easily comparable across mammals.

Despite these caveats, we can highlight certain proteins that are higher in bat serum than in humans, without an obvious technical artifactual explanation. These were identified using the ranks of proteins in the parallel analyzed human pool and those available on the Human Blood Atlas versus the ranks of proteins in the vampire bat dataset (Figure 2 ; Supplemental Table S5 ).

Broadly, these proteins fall into four general categories: innate immunity, circulating proteasome, anti-oxidants, and "other". We encourage readers to explore the full table for specific comparative proteins of interest (Supplemental Table S6 ). Proteasome related to proteins with bat and human ranks. PSMA1, proteasome subunit alpha type-1; PSMA2, proteasome subunit alpha type-2; PSMA3, proteasome subunit alpha type-3; PSMA4, proteasome subunit alpha type-4; PSMA5, proteasome subunit alpha type-5; PSMA6, proteasome subunit alpha type-6; PSMA7, proteasome subunit alpha type-7; PSMB1, proteasome subunit beta type-1; PSMB2, proteasome subunit beta type-2; PSMB3, proteasome subunit beta type-3; PSMB4, proteasome subunit beta type-4; PSMB5, proteasome subunit beta type-5; PSMB6, proteasome subunit beta type-6; PSMD2, 26S proteasome non-ATPase IMPDH2, inosine-5'-monophosphate dehydrogenase 2; ITIH2, inter-alpha-trypsin inhibitor heavy chain H2; ITIH3, inter-alpha-trypsin inhibitor heavy chain H3; ITIH4, inter-alpha-trypsin inhibitor heavy chain H4; KLK1, kallikrein-1; LIPG, endothelial lipase; PAFAH1B2, plateletactivating factor acetylhydrolase IB subunit beta; PCBP1, poly(rC)-binding protein 1; PF4, platelet factor 4; SERPINB10, serpin B10; SMPD1, sphingomyelin phosphodiesterase; SRI, sorcin; TFRC, transferrin receptor protein 1; TMPRSS9, transmembrane protease serine 9. All protein ranks are given in Supplemental Table S5, while just select proteins here are described in   Supplemental Table S6 .

Investigation of apparent differences in proteins related to innate immunity is important because vampire bats harbor diverse pathogens 22, 51, [54] [55] [56] 74 and because bats more generally appear to tolerate some viral infections without showing disease 4, 8, 20, 23 . In addition to the complement proteins described above, we identified notable proteins related to the innate immune system that are highly ranked in bat serum ( Figure 2C ). Given that some bats can constitutively express interferons (e.g., IFN-α in Pteropus alecto) 18 , it was not surprising to detect interferon-inducible proteins (e.g., guanylate-binding proteins GBP2, GBP6, and GBP7). Of note is that IFN-α and IFN-γ induce many similar proteins in a highly dynamic manner 75 . Specific to detected guanylate-binding proteins (GBPs), GBP2 was detected and shares antiviral properties with GBP5 (undetected), although circulating blood GBPs do not appear common in humans [76] [77] [78] . It would be interesting to determine if certain proteins are stratified into exosomes, similar to the IFN-induced antiviral proteome contained in macrophage-derived exosomes 79 . There were also proteins identified related to antiviral and antibacterial activity, notably relatively-high levels of CAMP (cathelicidin antimicrobial peptide). Finally, two scavenging proteins reported in human blood were ranked higher in bat serum: SFTPD (pulmonary surfactant-associated protein D) and DMBT1 (deleted in malignant brain tumors 1 protein). Though their functions are related, DMBT1 specifically binds viral and bacterial antigens 80, 81 and can reduce viral infectivity 82 .

The question remains whether these proteins confer a unique ability to keep pathogen virulence at bay or if these elevated protein levels instead indicate an active infection. Ongoing studies will continue to define the host-pathogen relationship in species such as the vampire bat.

In addition to focusing on classically immunological proteins, we observed 14 proteasome subunits ( Figure 2D ). Specifically, 13 of the 14 known 20S subunits (though missing PSMB7)

were observed along with one 26S component (PSMD2), indicating the presence of the circulating 20S proteasome 83, 84 . The lack of PSMB7 may be species-specific, similar to lower PSMB7 values reported across different mammal species 85 . Although circulating 20S proteasome is lower ranked in the Human Blood Atlas, it has been detected in human plasma, possibly within exosomes 86 . Given that our group has observed similarly abundant 20S proteasome subunits in other mammalian serum and plasma (e.g., California sea lion plasma proteome 87 ), circulating 20S proteasome is likely present in vampire bats and not a technical artifact of hemolysis or serum preparation. The 20S proteasome mediates proteasomal cleavage, with numerous cellular roles including response to disease and oxidative stress 84 . Interestingly, IFN-γ can induce formation of the immunoproteasome, which is the circulating 20S proteasome incorporated with β8, β9, and β10 subunits 83 . The immunoproteasome has diverse functions, including cleaving peptides into MHC class I epitopes 83 . The immunoproteasome is likely activated within hematopoietic cells, and may exist within extracellular vesicles though not necessarily circulating in the blood 84 . Though these additional immunoproteasome subunits were not observed, it is interesting to hypothesize the role of such high levels of circulating 20S

proteasome. These results demonstrate the potential of using mass spectrometry-based methods to study proteasomes, providing a basis for future immunological studies.

Beyond the possible uniqueness of bat immune systems is their ability to minimize or respond to oxidative stress. The evolution of flight in the chiropteran lineage was accompanied by mechanisms to minimize or repair the negative effects of oxidative stress generated by this metabolically costly activity, which may explain both the particular longevity of bats and their apparent viral tolerance 8, 88, 89 . For reference in Figure 2C , we have included glutathione peroxidase levels, which do not appear very different from levels in humans, but we note that there are higher levels of other redox-related proteins in vampire bats. Increased levels of peroxiredoxins (PRDX1, PRDX2, and PRDX6), superoxide dismutase (SOD1), and thioredoxin (TXN) indicate an enhanced capacity to scavenge or oppose free-radicals. High-levels of Rieske domain-containing protein (RFESD), which facilitates binding excess iron, may be related to the iron-rich, blood diet of vampire bats, although ferritin light chain (FTL) levels were found to be similar between bats and humans, ranked 154 and 336, respectively. Finally, vascular noninflammatory molecule proteins (VNN2 and VNN3) have been described as being involved in redox reactions via the production of cysteamine [90] [91] [92] . Overall, these results highlight that there may be increased oxidative resistance in vampire bats relative to humans; this pattern is likely to be conserved across bat species given the ubiquity of flight and long lifespans in bats, but this should be confirmed with broad comparative analyses.

In addition to proteins with obvious relation to known bat physiology, there are other interesting proteins that do not fit into a single category ( Figure 2D ). From this list, two sets of relationships are noteworthy: angiotensin-converting enzyme (ACE)/kallikrein 1 (KLK1) and hyaluronan-related proteins. Both ACE and KLK1 are higher in bats than humans, though their functions are antagonistic: kallikrein increases bradykinin, which vasodilates, while ACE cleaves bradykinin and thus may reduce vasodilation. In comparison, angiotensinogen (AGT), a source of the vasoconstrictor peptide angiotensin 2, is almost the same rank in bats as humans (ranked 29 and 25, respectively; Supplemental Table S5 ). Of note, given the entry of SARS-CoV-2 in humans, is the detection of TMPRSS9 as a mid-abundance protein in bat serum, though ACE2, which is detected in humans (rank 2517; Supplemental Table S5 ), was not present in bat serum. There are also increased hyaluronan-related proteins in vampire bat serum. The hyaluronan receptor CD44 is the same rank in bats and humans (Supplemental Table S5 ), though two hyaluronan carrier proteins (ITIH2 and ITIH3) and hyaluronidase 1 (HYAL1), which hydrolyzes hyaluronan, are higher in bats ( Figure 2F ). This last protein, HYAL1, is ranked 3024 in human plasma, versus 173 in vampire bat serum. It is unclear whether this indicates high levels of hyaluronan in bat serum, which in the naked-mole rat may confer anti-cancer properties 93 , or that these proteins are involved with keeping serum hyaluronan levels low in response to infection 94 . There are additional undiscussed proteins listed in this "other" category, as well as a full list of protein ranks compared to the Human Blood Atlas (Supplemental Table S5 -S6), that researchers are encouraged to browse for insight beyond the survey nature of this manuscript. It is interesting to postulate that vampire bat blood may have an anti-pathogenic phenotype, but it is unclear if this is in response to infection or constitutive. Similarly, given that many antiviral proteins are often involved in anti-cancer roles 95 , these two roles could plausibly be connected.

Data-independent acquisition (DIA) is an emerging technique in mass spectrometry-based proteomics, which in theory should allow deeper coverage than typical data-dependent acquisition (DDA)-based analysis by overcoming the stochastic nature of DDA data. We did not set out to compare the two approaches, but found this to be an interesting use-case of DIA to analyze undepleted serum. Detecting 361 proteins in undepleted serum using a relatively short 60 min gradient demonstrated that DIA-based proteomics of undepleted serum can scale reasonably well. Moreover, we took advantage of this technique to evaluate the presence of viral proteins. More generally, these peptides were detected using a relatively short gradient separation of undepleted serum, suggesting that a method enriching for viral particles prior to analysis could easily detect more viral proteins if present. Importantly, although PCR-based techniques are frequently used for viral surveillance in bats, a mass spectrometry-based approach could query a larger search space while maintaining acceptable detection limits. In cases where a specific viral taxon was targeted, mass spectrometry could provide a more accurate method of virus detection (e.g., as evidenced by mass spectrometry-based SARS-CoV-2 detection in humans [98] [99] [100] [101] ).

Targeted mass spectrometry methods using stable isotope-labeled peptides allow for creation of sensitive, precise, and accurate assays that avoid interferences that plague antibodybased methods. The first step of developing these targeted assays is empirically confirming the presence of predicted peptides, which is possible even in non-model species. For example, shotgun proteomics were first used to identify proteotypic adiponectin peptides in dolphin plasma, followed by validation of a parallel-reaction monitoring method to measure adiponectin at nmol/L levels using heavy isotope labeled peptides 102 . Any of the proteins identified in the current study can be measured using this technique. For example, PRM assays could be constructed for each of the 31 complement activation proteins listed, and this could be performed in high-throughput manner. These assays would be free from measurement interference (i.e., cross-reactivity seen in antibody assays) with all the benefits of accuracy and precision found in PRM-based mass spectrometry assays 103, 104 .

Our results highlight the power of modern proteomic techniques to provide new insights where other techniques might struggle. There is tremendous value in genomic and transcriptomic analyses; however, to understand the molecular landscape of blood, proteomic analysis is unique. This survey of the serum proteome of a small group of vampire bats provides a first look at the abundance of immunological proteins as well as proteins with unclear roles in the vampire bat phenotype. Moreover, we show that mass spectrometry-based viral detection in serum is possible and may be a viable tool for pathogen surveillance. Overall, these data can be used to develop targeted assays for future vampire bat research while also serving as a demonstration of the potential of proteomic studies for research on various topics in other bat species. For example, the physiology of white-nose syndrome and longevity are important topics that could benefit from investigations using modern biomolecular analytical techniques like proteomics. Future work will continue to investigate if proteins elevated in vampire bats compared to humans are similarly elevated in other mammals, or whether they are more common in wild animals than expected and not specific to a vampire bat phenotype. There is an ongoing need for comparative physiological studies to move beyond two-species comparisons and broaden our horizons across multiple clades of the tree of life.

Supplemental Table S1 Experimental key with sample metadata Supplemental 

Ecosystem Services Provided by Bats

Life History, Ecology and Longevity in Bats

Six Reference-Quality Genomes Reveal Evolution of Bat Adaptations

Bats Are an Untapped System for Understanding Microbiome Evolution in Mammals

Vampire Bats That Cooperate in the Lab Maintain Their Social Networks in the Wild

Host Phylogenetic Distance Drives Trends in Virus Virulence and Transmissibility across the Animal-human Interface

Bats as "special"reservoirs for Emerging Zoonotic Pathogens

Host and Viral Traits Predict Zoonotic Spillover from Mammals

Henipavirus Ecology Research Group. Pteropid Bats Are Confirmed as the Reservoir Hosts of Henipaviruses: A Comprehensive Experimental Study of Virus Transmission

Oral Shedding of Marburg Virus in Experimentally Infected Egyptian Fruit Bats (Rousettus Aegyptiacus)

Bats and Lyssaviruses

Bats Are Natural Reservoirs of SARS-like Coronaviruses

Ecological Dynamics of Emerging Bat Virus Spillover

Changing Resource Landscapes and Spillover of Henipaviruses

Experimental Hendra Virus Infectionin Pregnant Guinea-Pigs and Fruit Bats (Pteropus Poliocephalus)

Viral Zoonotic Risk Is Homogenous among Taxonomic Orders of Mammalian and Avian Reservoir Hosts

Contraction of the Type I IFN Locus and Unusual Constitutive Expression of IFN-α in Bats

Handling Stress and Sample Storage Are Associated with Weaker Complement-Mediated Bactericidal Ability in Birds but Not Bats

Immunological Control of Viral Infections in Bats and the Emergence of Viruses Highly Pathogenic to Humans

Temporal and Spatial Limitations in Global Surveillance for Bat Filoviruses and Henipaviruses

Demographic and Environmental Drivers of Metagenomic Viral Diversity in Vampire Bats

Accelerated Viral Dynamics in Bat Cell Lines, with Implications for Zoonotic Emergence

Guidelines of the American Society of Mammalogists for the Use of Wild Mammals in Research

A Species-Level Database of Life History

Antiviral Immune Responses of Bats: A Review

Immunology of Bats and Their Viruses: Challenges and Opportunities

Roosting Ecology and Variation in Adaptive and Innate Immune System Function in the Brazilian Free-Tailed Bat (Tadarida Brasiliensis)

Livestock Abundance Predicts Vampire Bat Demography, Immune Profiles and Bacterial Infection Risk

Effect of Sex and Reproductive Status on the Immunity of the Temperate Bat Myotis Daubentonii

Optimizing Viral Discovery in Bats

Ongoing Changes in Migration Phenology and Winter Residency at Bracken Bat Cave

Transmission or Within-Host Dynamics Driving Pulses of Zoonotic Viruses in Reservoir-Host Populations

Deciphering Serology to Understand the Ecology of Infectious Diseases in Wildlife

Transcriptomic Signatures of Tacaribe Virus-Infected Jamaican Fruit Bats

De Novo Transcriptome Reconstruction and Annotation of the Egyptian Rousette Bat

Using Noninvasive Metagenomics to Characterize Viral Communities from Wildlife

Metagenomic Analysis of the Viromes of Three North American Bat Species: Viral Diversity among Different Bat Species That Share a Common Habitat

Revisiting Biomarker Discovery by Plasma Proteomics

Plasma Proteomic Analysis of Active and Torpid Greater Mouse-Eared Bats

Plasma Proteomic Profiles Differ between European and North American Myotid Bats Colonized by Pseudogymnoascus Destructans

Vampirome": Transcriptome and Proteome Analysis of the Principal and Accessory Submaxillary Glands of the Vampire Bat Desmodus Rotundus, a Vector of Human Rabies

Maintenance of Neural Activities in Torpid Rhinolophus Ferrumequinum Bats Revealed by 2D Gel-Based Proteome Analysis

Acute Experimental Infection of Bats and Ferrets with Hendra Virus: Insights into the Early Host Response of the Reservoir Host and Susceptible Model Species

Natural History of Vampire Bats

Prey Preference of the Common Vampire Bat (Desmodus Rotundus, Chiroptera) Using Molecular Analysis

Foraging Choices of Vampire Bats in Diverse Landscapes: Potential Implications for Land-Use Change and Disease Transmission

Rabies Transmitted by Vampire Bats to Humans: An Emerging Zoonotic Disease in Latin America?

Enzootic and Epizootic Rabies Associated with Vampire Bats

Viral Diversity, Prey Preference, and Bartonella Prevalence in Desmodus Rotundus in Guatemala

Deforestation, Agricultural Intensification, and Farm Resilience in Northern Belize

Temporal Patterns of Vampire Bat Rabies and Host Connectivity in Belize. bioRxiv

Bats Host Major Mammalian Paramyxoviruses

Viral Communities Among Sympatric Vampire Bats and Cattle

Antibodies Against Henipa-Like Viruses in Brazilian Bats. Vector Borne Zoonotic Dis

Diversification of Mammalian Deltaviruses by Host Shifting

Erratum to: Alphacoronavirus in Urban Molossidae and Phyllostomidae Bats

A Coronavirus Detected in the Vampire Bat Desmodus Rotundus

Bats Are a Major Natural Reservoir for Hepaciviruses and Pegiviruses

Novel Herpesviruses in Neotropical Bats and Their Relationship with Other Members of the Herpesviridae Family

The Database of Bat-Associated Viruses

Observations of the Common Vampire Bat (Desmodus Rotundus) and the Hairy-Legged Vampire Bat (Diphylla Ecaudata) in Captivity

The PRIDE Database and Related Tools and Resources in 2019: Improving Support for Quantification Data

Complement and Its Role in Innate and Adaptive Immune Responses

Activation of the Complement System Generates Antibacterial Peptides

Complement: A Key System for Immune Surveillance and Homeostasis

Specific Alterations in Complement Protein Activity of Little Brown Myotis (Myotis Lucifugus) Hibernating in White-Nose Syndrome Affected Sites

Effects of Sewage-Water Contamination on the Immune Response of a Desert Bat

The Human Plasma Proteome: History, Character, and Diagnostic Prospects

The human blood in proteins detected in ms -The Human Protein Atlas

Plasma Proteome Profiling to Detect and Avoid Sample-Related Biases in Biomarker Studies

Epidemic Strain of Venezuelan Equine Encephalomyelitis Virus from a Vampire Bat Captured in Oaxaca

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression. Frontiers in Immunology

Guanylate Binding Protein (GBP) 5 Is an Interferon-Inducible Inhibitor of HIV-1

Guanylate-Binding Proteins 2 and 5 Exert Broad Antiviral Activity by Inhibiting Furin-Mediated Processing of Viral Envelope Proteins

Interferon-Induced Guanylate-Binding Proteins: Guardians of Host Defense in Health and Disease

Label-Free Proteomic Analysis of Exosomes Secreted from THP-1-Derived Macrophages Treated with IFN-α Identifies Antiviral Proteins Enriched in Exosomes

Deleted in Malignant Brain Tumors-1 Protein (DMBT1): A Pattern Recognition Receptor with Multiple Binding Sites

Identification of the Bacteria-Binding Peptide Domain on Salivary Agglutinin (gp-340/DMBT1), a Member of the Scavenger Receptor Cysteine-Rich Superfamily

Salivary Agglutinin and Lung Scavenger Receptor Cysteine-Rich Glycoprotein 340 Have Broad Anti-Influenza Activities and Interactions with Surfactant Protein D That Vary according to Donor Source and Sialylation

The Immunoproteasome and Viral Infection: A Complex Regulator of

The Contribution of the 20S Proteasome to Proteostasis

Cross-Species Proteomics in Analysis of Mammalian Sperm Proteins

Proteolytic Potential of the MSC Exosome Proteome: Implications for an Exosome-Mediated Delivery of Therapeutic Proteasome

Proteomic Analysis of Plasma from California Sea Lions (Zalophus Californianus) Reveals Apolipoprotein E as a Candidate Biomarker of Chronic Domoic Acid Toxicosis

Comparative Analysis of Bat Genomes Provides Insight into the Evolution of Flight and Immunity

Reduced Free-Radical Production and Extreme Longevity in the Little Brown Bat (Myotis Lucifugus) versus Two Non-Flying Mammals

the Natural Metabolite of Pantetheinase

Pantetheinase Activity of Membrane-Bound Vanin-1: Lack of Free Cysteamine in Tissues of Vanin-1 Deficient Mice

Vanin 1: Its Physiological Function and Role in Diseases

High-Molecular-Mass Hyaluronan Mediates the Cancer Resistance of the Naked Mole Rat

High Levels of Serum Hyaluronan Is an Early Predictor of Dengue Warning Signs and Perturbs Vascular Integrity

Interferon γ and Its Important Roles in Promoting and Inhibiting Spontaneous and Therapeutic Cancer Immunity

Adaptive Evolution of MERS-CoV to Species Variation in DPP4

Silico Approach toward the Identification of Unique Peptides from Viral Protein Infection: Application to COVID-19. bioRxiv

Targeted Proteomics for the Detection of SARS-CoV-2 Proteins. bioRxiv, 2020

Mass Spectrometric Identification of SARS-CoV-2 Proteins from Gargle Solution Samples of COVID-19 Patients

Proteotyping SARS-CoV-2 Virus from Nasopharyngeal Swabs: A Proof-of-Concept Focused on a 3 Min Mass Spectrometry Window

Ratiometric Measurements of Adiponectin by Mass Spectrometry in Bottlenose Dolphins (Tursiops Truncatus) with Iron Overload Reveal an Association with Insulin Resistance and Glucagon

Advances in Targeted Proteomics and Applications to Biomedical Research

Clinical Applications of Quantitative Proteomics Using Targeted and Untargeted Data-Independent Acquisition Techniques

For assistance with bat sampling logistics and research permits, we thank Brock Fenton, Mark Howells, Neil Duncan, and staff of the Lamanai Field Research Center. Identification of certain commercial equipment, instruments, software or materials does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the products identified are necessarily the best available for the purpose.

 Figure S1 . Distribution of relative standard deviations in technical replicate. One sample was injected in triplicate to evaluate technical performance of the method. Of the 361 proteins detected across the experiment, between 25 and 30 were filtered out, in total only 322 proteins were identified in all three injections. Using relative abundance from these 322 proteins, relative standard deviation (RSD) was calculated. The average RSD was 10.6 %, median RSD was 5.1 %, and 270 (83.9 % of 322) had an RSD < 20 %.