A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector1. Host-seeking female mosquitoes strongly prefer human odour over the odour of animals2,3, but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components4,5,6,7, making discrimination an interesting sensory coding challenge. Here we show that human and animal odours evoke activity in distinct combinations of olfactory glomeruli within the Ae. aegypti antennal lobe. One glomerulus in particular is strongly activated by human odour but responds weakly, or not at all, to animal odour. This human-sensitive glomerulus is selectively tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in human odour and which probably originate from unique human skin lipids. Using synthetic blends, we further demonstrate that signalling in the human-sensitive glomerulus significantly enhances long-range host-seeking behaviour in a wind tunnel, recapitulating preference for human over animal odours. Our research suggests that animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals targets for the design of next-generation mosquito-control strategies.
This is a preview of subscription content
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Code used for analyses and all unique biological materials generated in this study are available from the corresponding authors on request. Control code for the odour-delivery system, design files for the two-photon mosquito holder, and code for the XCMS-based odour analysis are available at GitHub (https://github.com/mcbridelab/Zhao_2020_HumanOdorRepresentation). For the analysis pipeline for volumetric antennal-lobe imaging, code is available at GitHub (https://github.com/rwth-lfb/Zhao_et_al).
Powell, J. R., Gloria-Soria, A. & Kotsakiozi, P. Recent history of Aedes aegypti: vector genomics and epidemiology records. BioScience 68, 854–860 (2018).
Gouck, H. K. Host preferences of various strains of Aedes aegypti and A. simpsoni as determined by an olfactometer. Bull. World Health Organ. 47, 680–683 (1972).
McBride, C. S. et al. Evolution of mosquito preference for humans linked to an odorant receptor. Nature 515, 222–227 (2014).
Dormont, L., Bessière, J.-M. & Cohuet, A. Human skin volatiles: a review. J. Chem. Ecol. 39, 569–578 (2013).
Jaleta, K. T., Hill, S. R., Birgersson, G., Tekie, H. & Ignell, R. Chicken volatiles repel host-seeking malaria mosquitoes. Malar. J. 15, 354 (2016).
Verhulst, N. O. et al. Do apes smell like humans? The role of skin bacteria and volatiles of primates in mosquito host selection. J. Exp. Biol. 221, jeb185959 (2018).
Syed, Z. & Leal, W. S. Acute olfactory response of Culex mosquitoes to a human- and bird-derived attractant. Proc. Natl Acad. Sci. USA 106, 18803–18808 (2009).
Malnic, B., Hirono, J., Sato, T. & Buck, L. B. Combinatorial receptor codes for odors. Cell 96, 713–723 (1999).
Chong, E. et al. Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. Science 368, eaba2357 (2020).
Wang, J. W., Wong, A. M., Flores, J., Vosshall, L. B. & Axel, R. Two-photon calcium imaging reveals an odor-evoked map of activity in the fly brain. Cell 112, 271–282 (2003).
Joerges, J., Küttner, A., Galizia, C. G. & Menzel, R. Representations of odours and odour mixtures visualized in the honeybee brain. Nature 387, 285–288 (1997).
Ruta, V. et al. A dimorphic pheromone circuit in Drosophila from sensory input to descending output. Nature 468, 686–690 (2010).
Stensmyr, M. C. et al. A conserved dedicated olfactory circuit for detecting harmful microbes in Drosophila. Cell 151, 1345–1357 (2012).
Demir, E. et al. The pheromone darcin drives a circuit for innate and reinforced behaviours. Nature 578, 137–141 (2020).
Nakagawa, T., Sakurai, T., Nishioka, T. & Touhara, K. Insect sex-pheromone signals mediated by specific combinations of olfactory receptors. Science 307, 1638–1642 (2005).
Knudsen, J. T., Eriksson, R., Gershenzon, J. & Ståhl, B. Diversity and distribution of floral scent. Bot. Rev. 72, 1 (2006).
Mansourian, S. et al. Fecal-derived phenol induces egg-laying aversion in Drosophila. Curr. Biol. 26, 2762–2769 (2016).
Lin, D. Y., Shea, S. D. & Katz, L. C. Representation of natural stimuli in the rodent main olfactory bulb. Neuron 50, 937–949 (2006).
Semmelhack, J. L. & Wang, J. W. Select Drosophila glomeruli mediate innate olfactory attraction and aversion. Nature 459, 218–223 (2009).
Riffell, J. A., Lei, H., Christensen, T. A. & Hildebrand, J. G. Characterization and coding of behaviorally significant odor mixtures. Curr. Biol. 19, 335–340 (2009).
Schubert, M., Hansson, B. S. & Sachse, S. The banana code-natural blend processing in the olfactory circuitry of Drosophila melanogaster. Front. Physiol. 5, 59 (2014).
Rose, N. H. et al. Climate and urbanization drive mosquito preference for humans. Curr. Biol. 30, 3570–3579 (2020).
Cardé, R. T. Multi-cue integration: how female mosquitoes locate a human host. Curr. Biol. 25, R793–R795 (2015).
Takken, W. & Verhulst, N. O. Host preferences of blood-feeding mosquitoes. Annu. Rev. Entomol. 58, 433–453 (2013).
Geier, M., Bosch, O. J. & Boeckh, J. Ammonia as an attractive component of host odour for the yellow fever mosquito, Aedes aegypti. Chem. Senses 24, 647–653 (1999).
Bernier, U. R., Kline, D. L., Allan, S. A. & Barnard, D. R. Laboratory comparison of Aedes aegypti attraction to human odors and to synthetic human odor compounds and blends. J. Am. Mosq. Control Assoc. 23, 288–293 (2007).
Mclver, S. B. Sensilla of mosquitoes (Diptera: Culicidae). J. Med. Entomol. 19, 489–535 (1982).
Vosshall, L. B. & Stocker, R. F. Molecular architecture of smell and taste in. Drosophila. Annu. Rev. Neurosci. 30, 505–533 (2007).
DeGennaro, M. et al. orco mutant mosquitoes lose strong preference for humans and are not repelled by volatile DEET. Nature 498, 487–491 (2013).
Kistler, K. E., Vosshall, L. B. & Matthews, B. J. Genome engineering with CRISPR-Cas9 in the mosquito Aedes aegypti. Cell Rep. 11, 51–60 (2015).
Riabinina, O. et al. Organization of olfactory centres in the malaria mosquito Anopheles gambiae. Nat. Commun. 7, 13010 (2016).
Vargo, A. M. & Foster, W. A. Responsiveness of female Aedes aegypti (Diptera: Culicidae) to flower extracts. J. Med. Entomol. 19, 710–718 (1982).
Brockerhoff, E. G. & Grant, G. G. Correction for differences in volatility among olfactory stimuli and effect on EAG responses of Dioryctria abietivorella to plant volatiles. J. Chem. Ecol. 25, 1353–1367 (1999).
Woolfenden, E. In Gas Chromatography (ed. Poole, C. F.) 235–289 (Elsevier, 2012).
Ignell, R., Dekker, T., Ghaninia, M. & Hansson, B. S. Neuronal architecture of the mosquito deutocerebrum. J. Comp. Neurol. 493, 207–240 (2005).
Cook, J. I. et al. Enantiomeric selectivity in behavioural and electrophysiological responses of Aedes aegypti and Culex quinquefasciatus mosquitoes. Bull. Entomol. Res. 101, 541–550 (2011).
Majeed, S., Hill, S. R., Birgersson, G. & Ignell, R. Detection and perception of generic host volatiles by mosquitoes modulate host preference: context dependence of (R)-1-octen-3-ol. R. Soc. Open Sci. 3, 160467 (2016).
Dekker, T., Steib, B., Cardé, R. T. & Geier, M. l-Lactic acid: a human-signifying host cue for the anthropophilic mosquito Anopheles gambiae. Med. Vet. Entomol. 16, 91–98 (2002).
Pitts, R. J., Derryberry, S. L., Zhang, Z. & Zwiebel, L. J. Variant ionotropic receptors in the malaria vector mosquito Anopheles gambiae tuned to amines and carboxylic acids. Sci Rep. 7, 40297 (2017).
Raji, J. I. et al. Aedes aegypti mosquitoes detect acidic volatiles found in human odor using the IR8a pathway. Curr. Biol. 29, 1253–1262 (2019).
Wisthaler, A. & Weschler, C. J. Reactions of ozone with human skin lipids: sources of carbonyls, dicarbonyls, and hydroxycarbonyls in indoor air. Proc. Natl Acad. Sci. USA 107, 6568–6575 (2010).
Huang, Z.-R., Lin, Y.-K. & Fang, J.-Y. Biological and pharmacological activities of squalene and related compounds: potential uses in cosmetic dermatology. Molecules 14, 540–554 (2009).
Prouty, S. M. & Pappas, A. In Lipids and Skin Health (ed. Pappas, A.) 139–157 (Springer, 2015).
He, X. & Slupsky, C. M. Metabolic fingerprint of dimethyl sulfone (DMSO2) in microbial–mammalian co-metabolism. J. Proteome Res. 13, 5281–5292 (2014).
Dekker, T. & Cardé, R. T. Moment-to-moment flight manoeuvres of the female yellow fever mosquito (Aedes aegypti L.) in response to plumes of carbon dioxide and human skin odour. J. Exp. Biol. 214, 3480–3494 (2011).
Obaldia, M. E. D. et al. Differential mosquito attraction to humans is associated with skin-derived carboxylic acid levels. Preprint at bioRxiv https://doi.org/10.1101/2022.01.05.475088 (2022).
Nicolaides, N. Skin lipids: their biochemical uniqueness. Science 186, 19–26 (1974).
Kligman, A. M. & Shelley, W. B. An investigation of the biology of the human sebaceous gland. J. Invest. Dermatol. 30, 99–125 (1958).
Green, S. C., Stewart, M. E. & Downing, D. T. Variation in sebum fatty acid composition among adult humans. J. Invest. Dermatol. 83, 114–117 (1984).
Pappas, A., Johnsen, S., Liu, J.-C. & Eisinger, M. Sebum analysis of individuals with and without acne. Dermatoendocrinol. 1, 157–161 (2009).
We thank V. Ruta, L. Vosshall, M. Murthy, J. Pillow, E. De Obaldia, E. Dennis, J. Breda, L. Yang, M. Mihalopoulos and members of the McBride laboratory for discussion and comments on the manuscript; D. Wevill for helping us adapt the thermal desorption system for stimulus delivery during neural imaging; R. Cohn and A. Gelperin for advice on odour-delivery systems; S. Sachse, A. Mohamed, D. Pacheco and D. Deutsch for guidance on antennal lobe imaging; H. Kazama for advice on two-photon data analysis; R. Harrell for mosquito embryo injections; S. Kotb for help with human odour collections; M. Khallaf for advice on XCMS odour-profile analysis; and staff at the Howell Living History Farm, Nassau Park Pavilion PetSmart and several dog owners for wool/hair samples. This work was funded in part by grants from the National Institutes of Health (NIDCD, R00DC012069; NIAID, DP2AI144246) to C.S.M.; the Swedish Research Council and Swedish University of Agricultural Sciences (senior career award) to R.I.; and the German Research Foundation (Deutsche Forschungsgemeinschaft, ME3737/3-1) to D.M. The C.S.M. laboratory is also supported by a Pew Scholar Award, a Searle Scholar Award, a Klingenstein-Simons Fellowship, a Rosalind Franklin New Investigator Award and the New York Stem Cell Foundation. C.S.M. is a New York Stem Cell Foundation–Robertson Investigator.
Princeton University has filed a patent (US 62/705,910, status pending) for using synthetic blends that mimic the response to human odour in the mosquito brain as mosquito attractants, listing C.S.M. and Z.Z. as inventors. The other authors declare no competing interests.
Peer review information
Nature thanks Olena Riabinina, Marcus Stensmyr and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 orco-T2A-QF2-QUAS-GCaMP6f labels chemosensory neurons in peripheral organs that project to the brain.
a–c, Antibody staining in female (a, b) and male (c) brains showing GCaMP in sensory neurons that innervate the antennal lobe (AL) and suboesophageal zone (SEZ). SEZ in (b) and the inset of (c) are viewed from posterior to better visualize GCaMP signal. d–g, Intrinsic GCaMP fluorescence in sensory neurons of adult female antenna (d), maxillary palp (e), labella (f) and larval antennae (g, arrowheads). Transmitted light image overlaid in (d–f). h–l, Antibody staining in brains of female mosquitoes with severed sensory organs (red in mosquito schematics). Severing right antenna only (h) led to loss of signal in all ipsilateral glomeruli except two in the posterior-medial region. Severing of both right antennae and right palp (i) led to loss of signal in all ipsilateral glomeruli. We therefore infer that Orco+ AL glomeruli are innervated by sensory neurons in the ipsilateral antenna (n~32 glomeruli) and palp (n = 2 glomeruli)51,52. Severing the tip of the proboscis (including the labella) led to loss of signal throughout the ventral SEZ (j), consistent with work in Anopheles gambiae indicating that Orco+ labellar neurons innervate this region31. However, labellum-less animals retained signal in an area of the dorsal SEZ recently termed the suboesophageal glomeruli (arrowheads in j) (https://www.mosquitobrains.org/). Signal in this dorsal region and corresponding ascending nerves was present in intact animals (k, arrowheads and arrows, respectively) but was lost when the ipsilateral legs were severed (l). This suggests that Ae. aegypti has Orco+ neurons on the legs that project to the SEZ, consistent with electrophysiological responses to olfactory stimuli on legs53. All scale bars 100 μm.
a–c, Analysis pipeline schematic. After registration and unsupervised segmentation of all brains in a given data set (a), one brain was chosen as the reference and glomeruli from other brains were matched to those in the reference either manually (b) or using an automated pipeline (c). Colours in (b, c) show matched glomeruli (unmatched in white). Manual matching was performed for analyses focused on only B (cyan), H (green), and A (orange) glomeruli (Fig. 3, 5). Automated matching, which provides a more global picture of activity but is less reliable for the three focal glomeruli, was used for the complementary analysis presented here (i–l). In both cases, matching was based on spatial position and response to 14 reference odorants. d, Reference odorants were chosen from among 60 candidates based on their ability to account for a large part of the observed signal variance/neural activity (see Methods). The 10 top-ranked odorants belonged to 8 different chemical classes. e, Response of glomeruli from one mosquito to the final 14 reference odorants. Note that we delivered reference odorants at high concentration (neat, 10−1, or 10−2 v/v dilutions) in order to activate as many glomeruli as possible. f, Evaluation of automated glomerulus matching. Glomeruli from 6 brains were matched as in (c). We then asked whether the matched glomeruli showed correlated responses to a new set of 13 test odorants. The plot shows the observed distribution of correlation coefficients across n = 28 sets of matched glomeruli (green) and 20 shuffled distributions where matches were reassigned at random (brown). Low correlations may be caused by mismatches or general lack of response by a given set of matched glomeruli to the test odorants. g, Same as (f) except showing the mean of the observed distribution (green line) and the distribution of means from 2000 shuffled datasets. h–l, Reanalyses of data presented in Fig. 3g–i relying in part or in whole on the automated pipeline. h, Human and animal odours were cleanly separated along the first three axes of an across-matrix PCA of unmatched signal clusters from all mosquitoes (see Methods). Symbols denote individual mosquitoes (n = 5); shades of red denote odour from different human subjects (n = 8). i–l, Human and animal odours were also cleanly separated in an analysis of signal clusters matched by the automated algorithm (c–g). Panel (i) shows signal clusters from the segmented antennal lobe of the reference mosquito, with key glomeruli highlighted. Panel (j) shows the mean normalized response to odour extracts (top) and select reference odorants (bottom) for those signal clusters (numbered across the bottom) that could be matched in the brains of at least 3 of 5 mosquito replicates. Panels (k, l) show a principal components analysis of data from (j). Note that the limited resolution of fast, volumetric imaging causes low level bleed through of signal from one glomerulus to proximal regions of adjacent glomeruli, especially along the z (depth) axis. This can make the delineation of adjacent glomeruli during unsupervised segmentation imperfect. Some glomeruli are split into two or more initial segments (e.g. two green H segments in (i) were initially split, but later merged by the automated algorithm due to correlated reference-odorant-responses, see Methods), while others show a shadow of the response pattern of their neighbors (e.g. clusters 11 and 12 shadow B in (j) and (l)). Nevertheless, the automated analysis supports the results of the manual analysis, showing that B, H, and A dominate host odour responses and contribute to the separation of human and animal odours. A fourth glomerulus (signal cluster #9) also contributes significantly and is highlighted in purple in (i–l). This glomerulus was obscured in the manual analysis because it is just posterior to B and has partially correlated responses to vertebrate odours. However, unlike B, it is strongly activated by the reference odorant 1-octen-3-ol (j), a known ligand of palp neurons36 that project to this posterior-medial region of the antennal lobe35 (Extended Data Fig. 1h–i).
a, Puff shape for hexanal, measured with a photoionization detector (PID) at the location of mosquito antennae in imaging set-up (n = 3 puffs). Time = 0 indicates the onset of focusing-trap desorption. It takes ~3 s for the desorbed odour to reach the mosquito. b, Puff shape for hexanal (orange), methyl laurate (green), and their mixture (blue), showing that the temporal dynamics of odour release are similar for odorants with markedly different volatility (n = 3 puffs each). c. Puff shape for human odour delivered via thermal desorption and detected using a PID. Note that the PID may not detect all blend components given their low individual concentrations. As demonstrated in (d, e), a few components are released over a longer period of time. d, GC–MS traces showing the composition of replicate puffs of human odour collected for a period of 10, 20, 40, or 85 s following the onset of trap desorption. Inset shows focusing-trap temperature across each interval. e, Fraction of major aldehydes that were released within the given intervals (calculated from (d)). Consistent with PID measurements (c), most major components were released within the first 10 s, including octanal and nonanal, but decanal took longer to fully desorb. Abundance of undecanal is too low for precise quantification, but it also appears to experience delayed release. f, Schematic of process for pooling (‘stacking’) odour samples and matching their concentrations before use in imaging. We stacked multiple collection tubes from the same individual human subject (or different individuals of the same animal species) to generate a single raw aliquot (brown). We then quantified 1/25th of each raw aliquot via GC–MS in order to inform the subsequent generation of concentration-matched aliquots (red) with the same total odour content (Fig. 2g). g, Concentration of five replicate puffs of hexanal delivered from each of four sample tubes (different colours) demonstrating repeatability of the delivered stimulus.
a, Response of three target glomeruli to 1X concentrations of the given stimuli (same data summarized in Fig. 3h, i). Coloured lines and grey shading show mean ± SEM response (n = 5 mosquitoes). Red arrows under each trace mark desorption (heating) onset. Y-axis scale bars indicate normalized df/f. The biphasic responses seen for B and H and the delayed responses seen for A are likely a technical artifact of thermal desorption odour delivery, resulting from delayed release of a few key compounds (see b–c). b, Overlay of H responses from (a), recoloured to distinguish the early (brown) and late (purple) peaks. Schematics below show the human-odour puff shape estimated with a PID (Extended Data Fig. 3c) and the inferred timing of release of three major aldehyde components (Extended Data Fig. 3d, e). c, Correlations between the area under the peaks in (b) and the relative abundance of major aldehydes in the respective stimuli. Dashed lines show linear regressions. The early H peaks are significantly correlated with the abundance of medium-chain aldehydes (which are fully released within the first 10 s), while late H peaks are correlated with the abundance of long-chain aldehydes (which take 20–40 s to fully desorb). Taken together, the biphasic response of the H glomerulus is therefore likely caused by the different release dynamics of medium- and long-chain aldehydes. The late peaks seen in B and A traces may also be caused by delayed release of strong activators. However, other temporal features of these responses, including the prolonged tonic nature of the A response, are biological, since we saw them both here and when single synthetic odorants were delivered in a more traditional way (Extended Data Fig. 7). To account for temporal artifacts, we always report glomerular responses as area under the full df/f curve (rather than peak df/f). We do not expect this to significantly impact our findings as the responses of olfactory sensory neurons to different compounds and their mixtures are mostly additive in insects21.
a, Analysis pipeline for GC-MS data. b, Total number of compounds found in each odour extract. c, Number of compounds found exclusively in the given combination of odour extracts. d, Cumulative distribution of odorants in each odour profile. e, Unscaled principal components analysis of human and animal odour profiles similar to Fig. 4b but including 2–4 replicate odour extractions for three of the human subjects. The subjects with replicate data are denoted by triangles, squares, and diamonds, respectively; all other subjects are represented by light red circles. f, P-values from Kolmogorov-Smirnov tests for a difference in the relative abundance of each odorant between humans and animals (with Benjamini-Hochberg multiple test correction). Values extend up or down from zero for human- or animal-biased odorants, respectively. Dashed lines mark P = 0.05. g, Violin plots showing on a log scale the relative abundance of odorants that passed the significance threshold in (f). h,i, Alternative analysis of human and animal odours using the program xcms, which matches the component ions of compounds across samples (rather than the compounds themselves, see Methods). Volcano plots show differences in abundance of all identified chromatogram components, with colour highlighting those corresponding to compounds that were (h) or were not (i) also significant in the original analysis in (f). P-values were calculated using Kolmogorov-Smirnov tests, corrected for multiple testing using the Benjamini-Hochberg procedure.
a, Design schematic. Filtered air is split into 5 streams, each regulated by a mass flow controller (MFC). The humidified carrier stream (grey) flows continuously through the mixing manifold (grey box) to the mosquito. Normally, the two control streams (green) are also flowing through 3-way valves to the manifold. Synthetic odorants and CO2 are delivered through the odour stream (red) and CO2 stream (brown), respectively. The odour stream has 20 odour channels (red) plus a bypass (blue). To puff the odorant in a given vial, the bypass closes, 2-way valves flanking the odour vial open, and the headspace of the odour vial is carried by the odour stream to a 3-way valve that diverts the stream from exhaust to the mixing manifold with a delay. Meanwhile, control stream 1 is diverted to exhaust to maintain a constant flow rate. When delivering CO2, the CO2 stream (fed by a carbogen tank) is similarly diverted to the mixing manifold and offset by control stream 2. The high-flow flush (blue, 2000 ml/min) opens between odour puffs to remove residual odorant from the system. Output of the thermal-desorption system used to deliver complex odours also joins the final mixing manifold. MFC, mass-flow controller; N.C., normally closed; N.O., normally open. See Methods for more detail. b, Shape of odour puffs delivered by the system, featuring fast rise/decay and stable peak height. Five replicate 3-second puffs of 2-heptanone (10−2 in paraffin oil) were aligned to the command onset (time = 0). c, Long-term stability of odour puffs delivered by the system. A 3-second puff of 2-heptanone (10−2) was delivered every 5 min for 75 min.
a, Mean response to major components of human odour delivered at their respective concentrations in a 1X human sample. Combo is a mix of all the individual components except acetoin. b, Mean response to individual odorants delivered at equal vapour-phase concentration (but see a few exceptions in d). Odorants are grouped according to those identified in our natural extracts (#1–32), biologically relevant compounds discussed in the literature (#33–45), compounds structurally similar to decanal/undecanal (#46–50), and high concentration reference odorants (#52–54). In both (a) and (b), responses from individual mosquitoes (n = 4–5) were normalized to the response of glomerulus H to decanal. Note that glomerular responses to single components are often prolonged, lasting well beyond the 3-second stimulus. This is consistent with recent single-sensillum recordings that found a prolonged response by olfactory sensory neurons to certain odorants, including aldehydes54. c–d, Vapour-phase concentration (estimated via GC-MS peak area, arbitrary units) of single-odorant puffs coming off the headspace of a 10−2 v/v liquid dilution (c) or an adjusted dilution calibrated individually for each odorant to generate a uniform target vapour-phase concentration (red lines) (d). Bars and black lines indicate mean ± SEM (n = 2–11 replicate puffs per odorant). Odorants ordered as in (b). Light-grey bars in (c) indicate high or low volatility odorants for which the 10−2 data are an extrapolation from a different initial, pre-calibration dilution (anywhere from neat to 10−6 v/v), which was necessary to match the dynamic range of the GC-MS. Note that dimethyl sulfone, p-cresol, and m-cresol were too insoluble/nonvolatile to achieve the target concentration, and geosmin was purposely delivered at a lower concentration (undetectable via our GC-MS set-up, headspace of a 10−3 liquid v/v dilution) to avoid contamination of our delivery system (as it readily adsorbs to surfaces). Lactic acid cannot be quantified via standard approaches and was placed in the odour vial undiluted.
a–d, Data supporting the automated analysis of host seeking presented in Fig. 6. a, We first assessed the utility of various flight parameters for the identification of host-seeking behaviour. We divided the flight trajectories of female mosquitoes exposed to human-worn socks versus odourless solvent into 10-second segments and then used a multivariable logistic regression to test the predictive power of each variable in discriminating between the two types of segments. Values of all variables were standardized as z-scores, making the plotted regression coefficients directly comparable. Dots and lines indicate mean ± SEM. The proportion of each 10-second segment that a mosquito spent in the odour plume had by far the most predictive power. b, Distribution of proportion-in-plume z-scores for human-worn sock (red) and solvent (grey) segments. A simple threshold of 0.5 (dotted red line) was used to identify ‘host seeking’ in Fig. 6h–i, l–m, but other thresholds (dotted black lines) produced similar results. c, d, Flight trajectories for individual mosquitoes visualized as the proportion of each consecutive 10-second segment spent in the plume. We tested n = 30 mosquitoes for each treatment, but trajectories are only shown for those that entered the filmed volume (Fig. 6f, j). e–h, Complementary analysis of wind-tunnel data that identifies host-seeking segments based on k-means clustering with all 5 flight variables (see Methods) rather than a simple proportion-in-plume threshold.
a, Antibody staining of mosquito antennal lobe in an animal expressing jGCaMP7s under the control of the brp pan-neuronal driver. All glomeruli are strongly labelled with jGCaMP7s. Scale bar 50 μm. b, AL reconstruction from confocal imaging highlighting Orco+ and Orco− glomeruli (top), five focal glomeruli discussed below (middle), and the viewing angle used in (c) (bottom). c, 3D renderings of the response of a single representative female mosquito to human, rat, and sheep odour. Dashed circles outline glomeruli that responded strongly at 5X. Arrowheads highlight key glomeruli, including an non-Orco glomerulus (magenta) adjacent to H that responded strongly to both human and animal odour in most replicate mosquitoes. d–g, Automated analysis of pan-neuronal imaging data, showing segmented antennal lobe of the reference mosquito (d), mean normalized response for all signal clusters that could be matched in the brains of at least 3 of 4 replicate mosquitoes (e), and principal components analysis of mean responses (f, g). As explained in Extended Data Fig. 2, the limited resolution of fast, volumetric imaging causes low-level bleed-through of signal from one glomerulus to adjacent regions of neighboring glomeruli, especially along the z (depth) axis. This can make the delineation of adjacent glomeruli during unsupervised segmentation imperfect, especially when all neurons express GCaMP as they do here. Some glomeruli are split into two or more initial segments (e.g. two green H segments in (d)), while others show a shadow of the response pattern of their neighbours. For example, signal cluster #30 shadows H, #19 shadows B, and #16 shadows #23 (magenta). To help readers more easily distinguish shadow signals from independent glomeruli, we have used dark and light shades of the same colour to highlight what we believe are source and shadow clusters, respectively, in (e) and (g). The overall pattern is consistent with the result from Orco+ imaging (Extended Data Fig. 2) in that four key Orco+ glomeruli contribute to host responses: B, H, A, and the 1-octen-3-ol-sensitive glomerulus posterior to B (signal cluster #3, purple). Importantly, H is still the only glomerulus that is selective for human odour. However, we now see two to three broadly host-sensitive signals coming from Orco− regions of the AL. Of these, the magenta glomerulus adjacent to H was the most consistent upon manual data inspection. It can be seen clearly in (c), but is less prominent in the automated analysis (signal cluster #23) due to the challenges of matching glomeruli across brains in this non-model species. Based on position, this glomerulus may be one of those that express the Ir8a co-receptor51,52.
Extended Data Fig. 10 Suggestive correlations between preference for individual humans and their aldehyde profiles.
a, Relationship between the extent to which a given human subject was ‘preferred’ (over animals in live-host preference assays) and the long-chain aldehyde content of the subject’s body odour. Preference estimates come from a reanalysis of the data in Fig. 1c, including human subject as a fixed effect. The long-chain aldehyde index is the ratio of long-chain aldehydes to total aliphatic aldehydes in a subject’s body odour. Dashed line indicates the average index across the n = 16 humans analysed in Fig. 4a. b, Same as (a), except x-axis now represents the difference between a subject’s long-chain aldehyde index and the average human index (blue arrows in a). Line shows linear regression.
This file contains Supplementary Methods and Supplementary References.
Proportional abundance of all quantified compounds for 22 human samples (from 16 distinct individuals, see Methods), 5 animal samples, and 2 nectar-related samples.
All compounds quantified in the stimulus-odour analysis (Fig. 4, Extended Data Fig. 5), used for single-odorant imaging (Fig. 5, Extended Data Fig. 7), or used as reference odorants (Extended Data Fig. 2d). Identifying GC-MS characteristics of analytes and purities/vendors of synthetic compounds are listed where applicable. ‘Solvent’ refers to the solvent used for reference odorants and single odorant stimuli. ‘Dilution’ columns indicate the v/v ratio used for the initial panel of candidate reference odorants (L), the final panel of reference odorants (M), human odorants presented to mosquitoes at 1X human concentration singly or in combination (N and O, respectively, Fig. 5b–d, Extended Data Fig. 7a), and odorants presented at equal concentration (P, Fig. 5f,g, Extended Data Fig. 7b).
Recipe for binary blends used in the wind tunnel experiments (Fig. 6, Extended Data Fig. 8).
About this article
Cite this article
Zhao, Z., Zung, J.L., Hinze, A. et al. Mosquito brains encode unique features of human odour to drive host seeking. Nature 605, 706–712 (2022). https://doi.org/10.1038/s41586-022-04675-4