The parabrachial nucleus (PBN), located at the junction of the midbrain and pons, relays sensory information from the periphery primarily to the forebrain, thereby playing a major role in informing the brain of both the internal state (interoception) and external conditions (exteroception) to facilitate responses to adverse conditions and help maintain homeostasis.

The earliest reference to the PBN was from Herrick, 1905, who implicated it in transmitting gustatory signals and later elaborated upon by Norgren and Leonard, 1971. The inputs and outputs of the PBN have been studied extensively using anterograde and retrograde methods (Fulwiler and Saper, 1984; Gauriau and Bernard, 2002; Krout and Loewy, 2000; Moga et al., 1990; Norgren, 1976; Saper and Loewy, 1980; Tokita et al., 2009). More recently, these studies have been supplemented using genetically engineered mice and stereotaxic delivery of viruses encoding fluorescent proteins to analyze the afferents and efferent projections of selected subsets of PBN neurons. The vagus transmits signals from internal organs, including the gastrointestinal system, to the nucleus tractus solitarius (NTS), which then projects to the PBN; thus, detection of visceral signals related to food and malaise depends on this circuit. Other internal organs, muscle, and bone transmit nociceptive signals via intermediary ganglia to the spinal cord and then directly to the PBN. Ascending fibers from the spinal cord relay peripheral temperature and pain signals directly to the PBN, while trigeminal neurons relay these signals from the face. In addition, blood-borne threats to homeostasis are detected by the area postrema and transmitted to the PBN (Zhang et al., 2021). Taste is transmitted from the tongue and palate via branches of the facial, petrosal, glossopharyngeal nerves to the rostral NTS and from there to the PBN. Additionally, calcium imaging and Fos-induction studies show that most sensory systems can activate neurons in the PBN (Campos et al., 2018; Carter et al., 2013; Kang et al., 2022), although the neuronal circuits involved are not well established. Thus, the PBN is a hub activated by a wide variety of sensory signals, which then report the state of the body to the other brain regions to elicit appropriate responses. Most of these afferent signals to the PBN are excitatory (glutamatergic), but there are also inhibitory, GABAergic inputs including those from the arcuate nucleus, bed nucleus of stria terminalis (BNST), and central nucleus of the amygdala (CEA). The PBN projects axons to the periaqueductal gray (PAG), extended amygdala (including the BNST, CEA, substantia innominata, SI), the cerebral cortex (primarily the insular cortex), thalamus, parasubthalamic nucleus (PSTN), hypothalamus, and medulla.

Pioneering neuroanatomical studies encouraged functional studies (lesions, pharmacological and viral/genetic interventions), which have substantiated the predictions that the PBN is important for responding to internal and external stimuli and maintaining homeostasis. Examples include taste, thermal sensation, visceral malaise, pain, itch, hypercapnia, breathing, cardiovascular control, arousal, hunger/satiety, thirst, sodium appetite, and alarm (Palmiter, 2018). The response of the PBN to these sensory modalities raises multiple questions: How many different neuron populations are there? Are specific neurons or subsets of neurons involved in transmitting each signal? Is there integration of sensory signals (crosstalk between neurons) within the PBN? Do individual neurons project axons to one target region or send collaterals to many brain regions? The location of neurons in the PBN that expresses distinct molecular markers will help address these questions.

The PBN is bisected by a fiber tract, the superior cerebellar peduncle (scp), resulting in subregions that are lateral or medial to the scp in primates. In rodents, the scp is rotated relative to that in primates such that so-called lateral regions are more dorsal to the scp, and medial regions are more ventral. Another fiber pathway, the ventral spinocerebellar tract (sctv), helps to define the dorsal border of the PBN in its caudal regions. The Kölliker-Fuse (KF) region (considered by some as part of the PBN), cuneiform nucleus, nucleus of the lateral lemniscus (NLL), mesencephalic trigeminal nucleus (MEV), and locus coeruleus (LC) are adjacent to it (Dong, 2008; Fulwiler and Saper, 1984; Paxinos and Franklin, 2019). In situ hybridization and immunohistochemistry studies have revealed that the PBN is primarily glutamatergic and expresses an abundance of different neuropeptides and neuropeptide receptors. These observations led to the creation of Cre-driver lines of transgenic mice that have been used to activate virally delivered, Cre-dependent genes to manipulate neuron activity and to visualize their axonal projections.

To define PBN cell types and gain insight into unique expression of signaling molecules and receptors, we adopted the single-cell RNA sequencing (scRNA-Seq) approach (Hashikawa et al., 2020; Macosko et al., 2015), which revealed 13 transcript-defined glutamatergic neuron types within the PBN proper along with sparsely interspersed GABAergic neurons. We then used in situ hybridization to anatomically locate the neurons within the PBN and Cre-driver lines of mice with viral expression of fluorescent proteins to establish the axonal projection patterns from the PBN of 21 Cre-driver lines of mice.

The goals of this project were to establish a catalog of neuronal cell types within the PBN, characterize their transcriptional profiles, determine their location within the PBN, and map their axonal projections. The results should facilitate more rigorous delineation of how specific PBN populations respond to and relay interoceptive and exteroceptive signals. As expected, the round tissue punches used to isolate the PBN included some adjacent regions; consequently, some of the UMAP clusters are not in the PBN. We identified 13 glutamatergic subclusters within the PBN, whereas the GABAergic neurons are scattered throughout. Some of the excitatory neurons (e.g., Calca, Pdyn, Tacr1) were already known to primarily occupy distinct locations within the PBN and have distinct functions, but the present results reveal that expression is not restricted to specific PBN subregions. Most of the PBN neurons express multiple neuropeptides and GPCR receptors; the co-expressed transcription factors likely play an important role in their cell-specific gene expression. Many of the neuropeptides expressed in the PBN, e.g., cholecystokinin, substance P, CGRP, somatostatin, prodynorphin, neurotensin, were known to be expressed in the PBN based on immunohistochemistry studies and confirmed by in situ hybridization (Hermanson et al., 1998; Saleh and Cechetto, 1996; Shimada et al., 1985) The overall axonal projections of the PBN neurons were established using anterograde tracers and confirmed using Slc17a6^Cre mice and injections of AAV carrying Cre-dependent fluorescent genes (Huang et al., 2021a). We provide detailed projection profiles from the PBN for many additional Cre-driver lines of mice that may generate ideas for testing their functions. The current data set provides a baseline for examining how the PBN changes during development and in response to environmental threats ranging from acute noxious events to chronic adverse conditions.

The PBN has been divided into 10 subregions based on rigorous Nissl cytoarchitectural criteria; subsequent anterograde and retrograde tracing studies revealed relatively distinct projections to and from different subregions of the PBN (see references in Introduction). As noted earlier, it is unfortunate that the nomenclature for different subregions of the PBN is not consistent in the literature, some regions are not shown at all in the AMBA, and a variety of abbreviations are used for the same subregions. Gene expression patterns provide an additional means to define these subregions as shown in Figure 4. Our results are consistent with those obtained by a new spatial-profiling method (PixelSeq) that was tested with PBN sections (Fu et al., 2022). We identified mRNAs with prominent expression in each of the PBN subregions except the PBme. Furthermore, what was once considered to be a unique population turns out to be more complex, e.g., both the Calca and Pdyn neurons are represented by two clusters based on scRNA-Seq analysis, and they could be subdivided even more by considering co-expression patterns of neuropeptides and other markers (Huang et al., 2021a, Huang et al., 2021b, Karthik et al., 2022). Whether these closely related clusters have distinct projections and functions needs to be established, e.g., are distinct Pdyn neurons involved in conveying temperature, nocifensive behaviors, and feeding responses? The significance of the tight clustering of Calca neurons in rostral sections, with few if any interspersed neurons in the core of the PBle, is not known; it is unlikely that gap junctions allow simultaneous activation because the activities of individual neurons expressing a fluorescent calcium indicator (GCaMP) are not synchronized (Chen et al., 2018).

In contrast to the glutamatergic neurons, the GABAergic neurons are rare and dispersed throughout the PBN (Raver et al., 2020). GABAergic neurons in the lateral PBN and caudal KF project axons to the brainstem (Geerling et al., 2017; Yokota et al., 2007). Chemogenetic activation of GABAergic neurons in the PBN region can inhibit the function of local glutamatergic neurons (Sun et al., 2020). We have shown using electrophysiology that AAV-directed expression ChR2 in Slc32a1^Cre neurons in the PBN region can inhibit Calca^tdT neurons (Chen and Cao, unpublished).

There are several limitations to the conclusions reached in this study. The choice of parameters used for clustering of scRNA-Seq data can affect the number of clusters, and sequencing depth can influence the reliability of co-expression for low-abundance transcripts. For example, the number of cells in a neuronal subcluster expressing a particular GPCR mRNA (e.g., Oprm1) was low based on scRNA-Seq analysis, whereas the signal from the Oprm1^Cre-driver line revealed many cells, suggesting that this mRNA was not detected in most to the cells that were sequenced. We obtained ~100,000 reads/neuron which may not have been enough to detect rare transcripts. A single mRNA/cell can maintain ~10,000 proteins with a half-life of 700 min at steady state (see ’Estimating mRNA and protein abundance per cell’ in Materials and Methods), which may be enough for many regulatory proteins. Deeper sequencing of more neurons and using multiple distinguishing probes may also reveal more cell types. Defining and distinguishing between different neuron types are challenging, requiring identification of master transcription factors along with multiple kinds of analysis including functional studies (Zeng, 2022). Thus, the results reported here will undoubtedly be refined by further investigation. Mice of both sexes were pooled for scRNA-Seq experiment, and only male mice were used for the HiPlex experiment, so future studies should consider this variable. Nevertheless, there was good, low-resolution correspondence among HiPlex, AMBA, and fluorescent protein expression from Cre-driver lines when transcripts were abundant, but we failed to detect a signal for some HiPlex probes (Fn1, Mylk, Slc35d3, Shisal2b) that were distinguishing genes based on scRNA-Seq analysis. There were also cases where predictions were not supported by HiPlex analysis (e.g., N5, N6, N18) even though scRNA-Seq indicated that these clusters express many of the same distinguishing transcription factors as other PBN clusters. Cre-driver lines are helpful for locating some neurons with low levels of gene expression (e.g., Ntsr1, Avpr1a) because, in principle, the action of a few Cre recombinase molecules is sufficient to activate robust expression from AAV carrying a Cre-dependent gene. When genes are expressed in the PBN as well as neighboring regions (e.g., Slc32a1, Phox2b), restricting AAV transduction to the PBN is challenging. It is also difficult to assure that any viral injection transduces all the relevant neurons within the PBN without doing an exhaustive analysis of each line. Animals and tissue sections were processed at different times, so variations in brightness could be due to aspects such as perfusion or staining quality rather than expression differences. The five coronal sections used for the HiPlex experiments did not include the most rostral region of the PBN, which explains our difficulty in locating clusters N4 and N9. We did not include probes for some genes that are known to be expressed in the PBN and detected by scRNA-Seq (Table 1), e.g., Penk (Engström et al., 2001), Grp (Karthik et al., 2022), Nmb (Huang et al., 2022), and Mc4r (Paues et al., 2006). It will be important to determine whether any of them are co-localized with the in situ probes that we used.

The last decade has seen extensive use of Cre-driver lines of mice and AAV carrying Cre-dependent effector genes to interrogate the functions of PBN neurons. One strategy uses Cre-drivers with restricted expression. For example, numerous studies with Calca^Cre_,Pdyn^Cre, and Tacr1^Cre mice have revealed their activation by a wide variety of real and potential threats, while their optogenetic or chemogenetic activation is generally aversive, and their inactivation ameliorates aversive responses to threats (references are included in Results, under N10, N15, N17). An alternative strategy uses Cre-driver mice with widespread expression in the PBN, e.g., Slc17a6^Cre, Cck^Cre, Oprm1^Cre, and Tac1^Cre, to assess behavioral and physiological consequences of their activation or inhibition (Barik et al., 2018; Cheng et al., 2020; Chiang et al., 2020; Liu et al., 2022; Sun et al., 2020). A problem with these Cre-drivers is the difficulty in restricting viral transduction to the PBN. Both approaches have flaws because it is rare for threats to activate only one cell type, and all the cells represented by the more widely expressed genes are rarely engaged by specific threats. Furthermore, activation of some PBN neurons can suppress the activity of others, e.g., activation of Tac1 neurons counteracts the outcomes of activating Calca neurons even though Tac1 and Calca are co-expressed in the PBle (Arthurs et al. manuscript submitted). This possibility complicates interpretation of results when groups of neurons are artificially manipulated. One solution to this problem is tagging and manipulating groups of neurons that are normally engaged by specific threats, e.g., FosTrap (DeNardo and Luo, 2017; Sakurai et al., 2016) techniques have been used to identify PBN neurons activated by pain or aversive odors (Liu et al., 2022; Rodriguez et al., 2017).

The broad outlines of axonal projections from the PBN were established decades ago by anterograde tracing studies (Fulwiler and Saper, 1984; Gauriau and Bernard, 2002; Krout and Loewy, 2000; Moga et al., 1990; Norgren and Leonard, 1971; Tokita et al., 2009) and confirmed by injection of AAV-expressing Cre-dependent fluorescent markers in the PBN of Slc17a6^Cre mice (Chiang et al., 2020; Huang et al., 2021a). The axonal tracts to the forebrain follow two main paths as they leave the PBN. The CTT pathway travels to the forebrain via the ventral thalamus, to the extended amygdala and cerebral cortex. The VP travels through the ventral tegmental area to the hypothalamus. A periventricular pathway passing through the PAG and innervates regions such as the PVT also exists (Huang et al., 2021b) but was not explored here because no line projected exclusively through it, and it was difficult to separate hypothalamic projections from those originating from the VP. A descending pathway innervates parts of the hindbrain including the NTS, pre-Bötzinger, and reticular regions. Calca neurons have axon collaterals that go to more than one brain region (Bowen et al., 2020). Most of the Cre-driver lines tested here resemble either the Calca neurons or the Pdyn neurons in their axonal projections; however, there are distinct differences in their innervation of forebrain targets that is revealed by synaptophysin. We identified Ntsr1 neurons as a restricted population in a distinct region of far rostral PBN with axons that travel along the VP to innervate mainly the VMH. This makes Ntsr1^Cre mice potentially useful for studying that connection in more detail.

The axonal inputs to specific clusters of PBN neurons are being established, either by retrograde rabies virus tracing studies starting with specific Cre-drivers, e.g., Calca^Cre (Liu et al., 2022; Rodriguez et al., 2017) or by candidate approaches starting with expression of AAV-DIO-ChR2 into distal sites of Cre-driver mouse lines mice and recording photoactivated currents in specific PBN neurons, e.g., input from Cck or Dbh neurons in the NTS to Calca neurons in the PBN (Roman et al., 2016), Oxt neurons in preoptic area to Oxtr neurons in PBN (Ryan et al., 2017), Slc17a6 or Slc32a1 inputs from BNST to Pdyn and Calca neurons in PBN (Luskin et al., 2021). Many other molecularly defined inputs to different subregions of the lateral PBN have been described, e.g., Tac1, Tacr1, and Gpr83 from spinal cord (Choi et al., 2020), Gfral and Glp1r from area postrema (Zhang et al., 2021), Calcr and Tac1 from NTS (Cheng et al., 2020; Xie et al., 2022), Slc17a6 and Dbh from LC (Yang et al., 2021), Slc6a3 from ventral tegmental area (Han et al., 2021), Slc32a1 from substantia nigra reticulata, Npy and Slc32a1 from arcuate nucleus (Alhadeff et al., 2018; Wu et al., 2009); Mc4r from the PVN (Garfield et al., 2015), Htr2a, Prkcd, or Sst, Pdyn, and Crh from CEA (Cai et al., 2014; Douglass et al., 2017; Raver et al., 2020). In the latter cases, knowing the locations and molecular identity of PBN clusters that they innervate would refine connectivity maps and provide insight into potential functions.

Our study highlights the diversity of cell types in the PBN, many of which reside in distinct subregions that align with prior anatomical tracing studies. We also mapped the PBN cell distribution and detailed brain-wide projections of 21 Cre-driver mouse lines. All these data are publicly available for download, and most of the mice have already been deposited at the Jackson Laboratory. This rich resource will inspire and inform future studies on the role and neurocircuitry of the PBN.

Raw and preprocessed data for scRNA-seq: NCBI GEO accession number GSE207708. Code for analysis of scRNA-Seq data: https://github.com/stuberlab/Pauli-Chen-Basiri-et-al-2022, (copy archived at swh:1:rev:8e974c4655cc4e4f1f3ce853b793af86f0e876bf). Raw and normalized data for RiboTag: NCBI GEO accession number GSE207153. Images from RNAscope and all tracing experiments: Zenodo DOI: https://doi.org/10.5281/zenodo.6707404.

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Author details

1. Jordan L Pauli

   Department of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, United States

   Contribution

   Data curation, Investigation, Visualization, Writing - review and editing

   Contributed equally with

   Jane Y Chen and Marcus L Basiri

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6276-3407

2. Jane Y Chen

   Department of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, United States

   Contribution

   Data curation, Investigation, Visualization, Project administration, Writing - review and editing

   Contributed equally with

   Jordan L Pauli and Marcus L Basiri

   For correspondence

   jychen@uw.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3986-8785

3. Marcus L Basiri

   1. Center for the Neurobiology of Addiction, Pain, and Emotion, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, United States
   2. Department of Pharmacology, University of Washington, Seattle, United States

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Writing - review and editing

   Contributed equally with

   Jordan L Pauli and Jane Y Chen

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4829-7187

4. Sekun Park

   Department of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, United States

   Contribution

   Data curation, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

5. Matthew E Carter

   Department of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1802-090X

6. Elisenda Sanz

   Department of Pharmacology, University of Washington, Seattle, United States

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7932-8556

7. G Stanley McKnight

   Department of Pharmacology, University of Washington, Seattle, United States

   Contribution

   Supervision, Funding acquisition

   Competing interests

   No competing interests declared

8. Garret D Stuber

   1. Center for the Neurobiology of Addiction, Pain, and Emotion, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, United States
   2. Department of Pharmacology, University of Washington, Seattle, United States

   Contribution

   Supervision, Funding acquisition, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1730-4855

9. Richard D Palmiter

   Department of Biochemistry, Howard Hughes Medical Institute, University of Washington, Seattle, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   palmiter@uw.edu

   Competing interests

   Reviewing editor, eLife

   "This ORCID iD identifies the author of this article:" 0000-0001-6587-0582

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