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OPEN

Rheological analysis of sputum
from patients with chronic
bronchial diseases
Jérémy Patarin1, Étienne Ghiringhelli1, Guillaume Darsy1, Martinien Obamba1,
Philippe Bochu1, Boubou Camara2, Sébastien Quétant2, Jean‑Luc Cracowski3,
Claire Cracowski3 & Matthieu Robert de Saint Vincent1*
Bronchial diseases are characterised by the weak efficiency of mucus transport through the lower
airways, leading in some cases to the muco-obstruction of bronchi. It has been hypothesised that thisloss of clearance results from alterations in the mucus rheology, which are reflected in sputum samples
collected from patients, making sputum rheology a possible biophysical marker of these diseases andtheir evolution. However, previous rheological studies have focused on quasi-static viscoelastic (linear
storage and loss moduli) properties only, which are not representative of the mucus mobilisation
within the respiratory tract. In this paper, we extend this approach further, by analysing both quasistatic and some dynamic (flow point) properties, to assess their usability and relative performancein characterising several chronic bronchial diseases (asthma, chronic obstructive pulmonary disease,and cystic fibrosis) and distinguishing them from healthy subjects. We demonstrate that pathologies
influence substantially the linear and flow properties. Linear moduli are weakly condition-specific andeven though the corresponding ranges overlap, distinct levels can be identified. This directly relates
to the specific mucus structure in each case. In contrast, the flow point is found to strongly increase in
muco-obstructive diseases, which may reflect the complete failure of mucociliary clearance causing
episodic obstructions. These results suggest that the analysis of quasi-static and dynamic regimes
in sputum rheology is in fact useful as these regimes provide complementary markers of chronic
bronchial diseases.
Chronic bronchial diseases, viz. asthma, chronic obstructive pulmonary disease (COPD), bronchiectasis, cystic
fibrosis (CF) to cite a few, represent a major and growing public health ­issue1. In the lower airways, the innersurface of bronchi is covered by mucus, a hydrated (≃ 98% water) cross-linked network of high molecular weightmucins which acts as a physical barrier to inhaled contaminants and is continuously secreted and d­ igested2.
Although very distinct in origin and mechanisms, chronic bronchial diseases share as common feature a failureof mucus transport, which may lead to mucus overproduction and/or accumulation. In greater or lesser amount,according to their condition, patients produce sputum, a mucus solution with biological material (leucocytes,
bacteria, proteins, DNA) therein, and/or partly dehydrated. However, these mucus releases are not always sufficient to contain the accumulation. In the so-called muco-obstructive ­diseases3 (COPD, bronchiectasis, CF,
primary ciliary dyskinesia) inflammations and/or infections episodically cause acute crises, called exacerbations.
Since these respiratory diseases are caused by altered mucus transport, a tempting hypothesis is that mucus
rheological properties are altered; this is indeed etymologically apparent from the synonym of cystic fibrosis,‘mucoviscidosis’, which stands for ‘viscous mucosities’ in reference to the very thick appearance of sputa. This
assumption motivated pioneer investigations on mucus viscoelasticity starting from the late ­1960s4–7. The intuited
link between sputum rheology and the symptomatic difficulty to clear airways was empirically ­confirmed8–12,
and supported the development of therapies relying on mucus fl­ uidisation13–17 or mechanical stimulation (physiotherapy, exercise)18,19 to improve mucus drainage.
1
Rheonova, domaine universitaire, 1270 rue de la piscine, 38400 Saint Martin d’Hères, France. 2Service
Hospitalo‑Universitaire de Pneumologie et Physiologie, Pôle Thorax et Vaisseaux, Centre hospitalier universitairede Grenoble-Alpes, Boulevard de la Chantourne, 38700 La Tronche, France. 3Inserm CIC1406, Centre hospitalieruniversitaire de Grenoble-Alpes, Boulevard de la Chantourne, 38700 La Tronche, France. *email: rdsv@
rheonova.fr

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More recently, the potential of sputum rheology as a direct biomarker in CF was brought forward, especially by linking the abnormal viscoelastic properties of CF sputum to secondary infection and ­inflammation20.
Macroscopically, the viscoelastic anomaly is attributed to purulence, as mucoid (i.e., not infected or inflamed)
CF sputum is essentially indistinguishable from healthy sputum, even though the microstructure is ­altered21,22.
Tomaiuolo et al. correlated the bacterial charge with viscoelastic properties in sputa collected from CF patientsand showed that the dominant bacterial species involved lead to specific rheological r­ esponses23. Very recently,
a longitudinal study specifically evidenced the rheological signature of e­ xacerbations24, showing a strong (andreversible) increase of the storage and loss moduli during the crisis. The exacerbation state also produces ameasurable signature in spirometry, through a transient decrease in FEV1 , as well as in sputum composition,
through a transient increase in solid fraction, but these changes were not considered statistically significant. These
correlations support the idea that sputum viscoelasticity could directly characterise the severity and evolutionof CF, which raises the practical question of the stability of this biomarker in time. A very recent study actually concluded to the poor statistical reliability of repeated measurements on a group of patients, based on low
values of the intraclass correlation ­coefficients25. However, the measurement variability was not compared to
the rheological modifications characterising a clinical event. It is thus difficult to conclude on whether the poorcorrelation reported actually represents a practical limit to sputum rheology in biomedical studies.
Overall, the potential of rheological biomarkers in CF is increasingly acknowledged in the biomedical researchcommunity, and it is tempting to generalise this approach to other chronic bronchial diseases if the hypothesis ofseverity-dependent mucus properties remains true. A first step in this direction was undertaken by Serisier et al.,
who compared the viscoelasticity levels of CF, COPD, and normal sputa (healthy subjects)20. In CF, mucoid sputa
have viscoelastic moduli statistically comparable to those of healthy subjects. In contrast, COPD patients featuresignificantly higher viscoelastic levels even in the absence of inflammation. This result suggests that the linear
viscoelastic moduli may not represent characteristic markers of the pathologies and should be complemented
with a refined rheological analysis. Indeed, although the stresses and strains involved in bronchial obstruction are
not quantified, and possibly not even common to all obstructive diseases, clearance in obstructed states involves
strong mechanical solicitations to the mucus when patients expectorate. ­Cough26, for instance, is a turbulent
air drag with air flows as high as 100 m s−1. Mucus mobilisation in this regime involves rupturing mechanisms,
which depend on properties such as adhesion and c­ ohesion27, and thus clearly overcome quasi-static shear characterised by the storage and loss moduli. It is therefore tempting to explore the dynamic rheological behaviourof sputum over a wider range of solicitations, towards plastic or even flow regimes, as a first step to assess therelevance and feasibility of large-deformation rheological measurements.
The objective of the present paper is to assess the usability and relative performance, in the general context
of chronic bronchial diseases (muco-obstructive or not), of easy-to-access rheological quantities representativeof the rich rheological behaviour of sputum. To this aim, we characterise sputum samples produced by healthy
volunteers, patients with asthma, COPD, and CF, through quick analyses of fresh samples performed in a clinicalenvironment. We first define rheological observables characteristic of the small- (linear viscoelastic region, LVR)
and large-deformation (flow point) regimes. We then evaluate quantitatively the stability (evolution in time) of
these rheological parameters, and confirm the existence of a baseline, patient-dependent level. We also characterise the rheological influence of induction, a standard procedure to help sputum ­production28. Comparing theserheological quantities for the four considered populations, we finally demonstrate that they follow segmented
viscoelastic levels, and that the flow point very robustly distinguishes the muco-obstructive conditions.

Results

Strain sweeps straightforwardly characterise sputum rheology.

The structural and dynamic
properties of a sample are solicited in the quasi-static and flow regimes, respectively. To assess both successively
on sputum samples, we impose a strain sweep in increasing strain ramps from 0.9% up to 3000%. Figure 1 presents, for each of the four conditions considered, a representative example of the evolution of the storage (G′ ) andloss (G′′ ) moduli with strain. The rheological behaviour, reminiscent of soft visco-elasto-plastic solids (gels), isqualitatively similar irrespective of the condition tested. At low strain (generally when γ  10%), G′ and G′′ areconstant and thus represent the quasi-static properties of the material, when the structure remains essentiallyintact under strain (LVR). In sputa, the mechanical response is dominated by elasticity, G′ > G′′ , with a damping
ratio, tan δ = G′′ /G′ , typically within 0.25–0.45. The frequency dependence of the moduli follows a weak powerlaw with comparable exponents for G′ and G′′ (see Supplementary Material S1, Fig. S1), as recently observed in
COPD ­sputum29 as well as cultured mucus ­samples30.
When increasing the strain beyond about 10%, G′ and G′′ both decrease and eventually converge above∼ 1000% strain. In this regime, the network structure begins to irreversibly disentangle (plastic regime). The
extent, amplitude and shape of this regime vary from sample to sample, irrespective of the patient’s condition.
In most cases, G′′ decreases at a rate similar to G′ as the shear increases, but it sometimes remains almost constant over the whole plastic range (see Healthy case in Fig. 1), and/or raises and overshoots G′ at the end of thisrange (see COPD case in Fig. 1). This alternative behaviour reflects the gradual unfolding and alignment of the
microstructural elements along the shear direction, leading to increased dissipation. As a consequence of thisvariability in the plastic regime, no general rule can be observed regarding the evolution of tan δ, which either
remains roughly constant or gradually increases. The crossover point (when the strain γ = γc , typically within
500–3000%) defines the onset of a viscosity-dominated regime, i.e., flow. Note that this critical point could notalways be reached and/or measured reliably as some samples tend to spread out of the measuring cell at highshear.
Besides the general behaviour illustrated in Fig. 1, a minority of samples feature an unexpectedly viscous
response with weak critical strain γc values, around 100% or below. These fluid-like samples are suspected to be

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Figure 1.  Sputum rheological response to strain. Evolution of the storage (G′ , ) and loss (G′′ , ) moduli, andthe damping ratio (tan δ = G′ /G′′ , •) with the applied strain, obtained during a strain sweep in oscillatory mode
(frequency 0.6 Hz). Open symbols: values obtained in frequency sweeps at 5% and 10% strain, respectively.
mostly constituted of saliva and thus ruled out—we set a cutoff value γc = 500%, midway between saliva-dominated and sputum-dominated behaviours, below which a sample is considered polluted. Besides, several samples(especially among asthmatics and COPD patients) seem to feature a crossover while G′ and G′′ both increase very
abruptly beyond 1000% strain (Fig. S2). The physical meaning of this apparent abrupt transition is not identified and it likely relates to an instrumental artefact. To avoid the risk of undue comparisons, samples featuring
this unusual behaviour are set apart from the analysis and discussed separately in Supplementary Material S2.
To sum up, two characteristic strain responses of sputum samples can be extracted unambiguously in the
LVR and at the onset of flow (crossover point). We extract the value of G′ and G′′ at γ = 5% (see Methods), which
generally falls within (or close to) this first regime and can be measured with reasonable accuracy. Since thelinear response is essentially elastic, we focus on G′ ; tan δ is also systematically reported as a structural markerof the storage versus dissipation balance.
At the crossover, the value of the modulus, G′ = G′′ = Gc′ allows us to√calculate the critical stress, σc = 2Gc′ γc , which physically corresponds to the stress needed to make the material flow. We now analyse the robustness of these rheological quantities to characterise a patient’s condition.

Sputum rheology is temporally stable.

The perspective of using sputum rheology in biomedical or
clinical research relies on the assumption that the values of the measured rheological quantities are patientspecific, and therefore stable over relatively short times, as long as the patient remains stable.
′ and σ measured on consecutive measurements, performed
Figure 2 shows the individual evolution of G5%con aliquots from the same sample (replicates) on the one hand, and on consecutive samples produced two days
apart by the same stable patient on the other hand. The symbols and colours identify individual COPD (top)and CF patients (bottom). In both cases, individual values spread within up to two orders of magnitude in boththe linear and crossover regimes. Considering samples individually, Fig. 2 shows that, with few exceptions,variations between consecutive replicates remain tight within a factor of two (i.e., a variation factor comprised
between 0.5 and 2, as delimited by the shaded area). The two-days variations are calculated by comparing, foreach patient, the average of replicates in visits 1 and 2. Although few patients feature an increase or decrease bya factor of up to 4–5 in isolated cases, a large majority of them are actually stable (within the shaded area), sothat the typical relative variations between replicates (same sample) and between visits (same patient, distinct
samples) are comparable in amplitude.
The amplitude of the observed variations is, in all cases, very small in comparison with the expected signatureof major clinical events. In the linear regime, G′ was reported to consistently increase by a factor of around 5
in CF patients when experiencing an exacerbation, and symmetrically decrease back to the base level after the­event24: this modification of sputum rheology is much bigger than the typical variations observed in the present
study. Consecutive measurements can thus be considered stable, both at the sample and at the patient levels,
when considering the characterisation of major events.
To assess the statistical robustness of the measurement stability, we performed correlation tests between
consecutive replicates and visits when available. Table 1 gathers the Spearman correlation coefficient and the corresponding p-value obtained in each case (see also Supplementary Material S3, Table S1). Consecutive replicates(first row) are significantly correlated in all cases ( p < 0.05), which confirms the strong stability of measurements
at the sample level. This stability shows that, within the duration of the set of measurements (up to ∼ 1 h after
expectoration), sputum samples do not evolve substantially, and repeated comparative measurements can bemeaningful if enough sample can be collected.
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patients (bottom). Each connected group of symbols corresponds to a single sputum sample; symbols areassociated to individual patients. The horizontal bar in each replicate is the geometric mean. The variation
factors are the ratios of replicates n + 1 and n taken individually, and of replicated values in each visit (bar: meanvariation factor). The shaded area delimits variations (increase or reduction) by a factor smaller than two.

Visit 1, Replicate 1 versus′
COPD, G5%

COPD, σc′
CF, G5%CF, σcVisit 1, Replicate 2

ρ

0.918

0.889

0.694

0.675

p

< 0.0001****0.017*

0.008**

0.048*

N

12

6

9

7

Visit 2, Replicate 1

ρ

0.556

0.090

1.000

1.000

p

0.012*

0.683

0.333

0.333

N

11

5

3

3

Table 1.  Results of Spearman correlation tests between the (Visit 1, Replicate 1), (Visit 1, Replicate 2)and (Visit 2, Replicate 1) cases: Spearman coefficient ρ , p-value and sample size N. * p < 0.05; ** p < 0.01;**** p < 0.0001.

′ in COPD patients. In all other
Between visits (second row), a significant correlation is only found for G5%
cases, correlations cannot be confirmed due to the very small population size ( N  5) which does not allow us
to draw a statistically robust conclusion. However, considering the moderate two-days variations observed in the′
majority of samples (Fig. 2), and the statistically robust two-days correlation found in a more favourable case (G5%in COPD, with N = 11), it is sensible to anticipate the global two-days stability of rheological measurements.
This result seems to contradict the conclusions of Radtke et al., who rather concluded that the stability ofrheological measurements cannot be statistically ­confirmed25. However, their study assessed the measurement
stability over a longer time (7 ± 1 days, with an intermediate visit), which makes clinical evolution increasingly
likely. Noteworthy, the median values of elastic moduli reported are very similar in the first two visits, but substantially smaller in the third, with poor overlap of the distributions. This study thus does not jeopardise ourconclusion that sputum can be considered stable within 2 days.
Sputum rheological stability implies that baseline levels can be defined and considered representative of thestable patient with a given condition. Of course, the robustness of rheological characterisation also relies on

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Figure 3.  Effect of induction on sputum rheology. Left: Evolution of the linear storage modulus, G5%ratio, tan δ5%, and critical stress, σc , before (t = 0, spontaneous expectoration) and after nebulisation of 4.5%
HSS, for individual COPD patients. Right: Same rheological parameters, comparing spontaneous expectoration
to 4.5% HSS nebulisation (10 min) and to 2.5 mL rhDNase in CF patients. Each connected group of symbols
corresponds to consecutive sputum samples collected from the same individual patient; each symbol is a meanover consecutive replicates when available. Horizontal bars: geometric (G′ , σc ) or arithmetic (tan δ) mean overthe corresponding populations. * p < 0.05; ** p < 0.01.

standardised protocols, especially during sputum production. In light of this, we now evaluate how rheologicalmeasurements are affected by a pre-collection induction.

Inducing sputum modifies its rheology. A possible practical limitation to sputum analyses is the ability
to collect sufficient amount of sample. As a matter of fact, spontaneous production of sputum is only possible
with over-secreting patients. To help patients expectorate, ­induction28, which consists in nebulising saline solutions with a mouthpiece, is common practice; it is actually necessary in cases when patients cannot expectorate spontaneously. However, as saline solutions are mucus hydrators, they likely affect sputum ­rheology17. We
assessed this effect quantitatively on both COPD and CF sputa, as these two populations were able to expectorate
spontaneously.
′ , tan δ
The left panel of Fig. 3 presents the evolution of G5%
5% and σc measured on COPD sputa, collected
through several consecutive expectorations before (t = 0) and during nebulisation of 4.5% hypertonic saline solu′ and σ respectively decrease by a factor of 2.9 ± 1.8 ( p = 0.009) and 3.4 ± 2.3 ( p = 0.246)
tion (HSS). Both G5%cduring the first 10 minutes, and then, on average, saturate. The initial trend is also consistently observed at theindividual patient level, except for patients whose sputum already had low rheological base levels. The evolutionof tan δ5% is more contrasted, although the average trend shows a slight increase, from 0.31 to 0.37 ( p = 0.043),
which could reflect a mild hydrating effect. Cystic Fibrosis sputa (Fig. 3, right panel) also feature reductions, by′ and σ through HSS induction, and contrasted
factors of 2.6 ± 1.1 ( p = 0.014) and 1.9 ± 0.7 ( p = 0.061), of G5%
cchanges in tan δ5% ( p = 0.836 ). HSS nebulisation thus similarly leads to a substantial reduction of the linear
and crossover rheological parameters in both pathologies, although more pronounced in COPD than in CF.
For the sake of comparison, recombinant human DNase I (rhDNase, Pulmozyme) was administered to the
CF patients during their second visit. RhDNase is a mucolytic drug, widely used in CF treatment, which weakens
purulent mucus by cleaving D­ NA13,15. As illustrated in the right panel of Fig. 3, rhDNase affects sputum rheol′ and σ are reduced by a factor of 1.9 ± 1.0 and 2.2 ± 1.6
ogy in a way quantitatively comparable to HSS (G5%crespectively; p = 0.053 and p = 0.049).
In summary, HSS induction unambiguously leads to a substantial weakening of the sputum rheologicalbaseline in COPD and CF patients, largely exceeding the measurement variability. Induction should therefore
be considered as an influential parameter when comparing rheological measurements in sputa. Consequently,
in view of a standardised protocol, even over-secreting patients should undertake induction if their sputum
properties are to be compared to those of healthy subjects.
Sputum rheology characterises chronic bronchial diseases. We now turn back to the comparisonof rheological properties for patients with distinct conditions. Considering that a patient can be characterised by
the baseline level of his/her sputum rheology, we now wonder if this level is itself determined by the disease. We
thus build, for each rheological quantity, the distribution of patients levels in each population.
Given the stability of rheological measurements, each patient’s level is defined by averaging all values obtained
after HSS nebulisation. This gives us, for each rheological quantity, a single value per patient and avoids overweighting the most productive ones. The upper panel of Fig. 4 presents these data in the form of probability′ , tan δ and σ for the four populations of healthy subjects, asthmatics, COPD, and CF patients. The
plots of G5%c5%cumulated probability over all measured quantities is very well adjusted with a cumulative distribution function
E(X) of the form

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Figure 4.  Rheological levels in several bronchial conditions. Top: probability plots of the values of G5%
5%
and σc measured from subjects with the four conditions (healthy, •; asthma, ; COPD, ; CF, ). Each symbol
corresponds to the per-patient average value after HSS nebulisation; solid line is a fit with Eq. (1). Bottom:
expected values and standard deviations ( X0 ± ) of these rheological parameters, compared by condition, as afunction of the corresponding relative FEV1 (mean ± standard deviation). Filled and open symbols depict HSSinduced and spontaneous sputa, respectively. ** p < 0.01; *** p < 0.001.

E(X) =
X − X0N
1 + erf √
,
2
2�

(1)

x
2
′ , tan δ and log σ respectively; X and  arewith erf (x) = √1π −x e−t dt the error function, and X = log G5%c05%respectively the expected value and the standard deviation. With these variables, the functional form of E(X)
′ and σ on the other hand, are normal and logimplies that the distributions of tan δ5% on the one hand, and G5%
cnormal, respectively. The calculated expected values ( X0) and standard deviations () are depicted in the lower
panel of Fig. 4; Table 2 summarises the corresponding physical quantities for the whole set of measured rheological parameters.
Figure 4 confirms that sputum rheology can distinguish pathologies. In the linear regime, the elastic moduli
decrease as the mean relative FEV1 values increase, and nicely succeed each other from healthy (expected value,G′ = 0.14 Pa ), asthmatics (0.25 Pa), COPD (0.43 Pa) up to CF patients (0.84 Pa), illustrating a gradually stiffer
mucus. However, some overlap exists and only CF and healthy sputa are statistically distinct ( p < 0.01). The
damping ratio tan δ remains consistently around 0.35. Thus, even if the gel-type structure of mucus is likely
distinct in each condition, which is reflected macroscopically through the distinct G′ values, the influence of dissipation is essentially identical. No condition distinguishes by an intrinsically ‘more fluid’ or ‘more solid’ mucus.
At the crossover, the four conditions follow the same ranking sequence than observed on linear moduli, witha smaller overlap between populations. Especially, the σc values corresponding to COPD and CF patients are
distinctly higher (by a factor of 10–20) than those measured in healthy subjects (3.61 and 6.34 Pa compared to
0.27 Pa; p < 0.01 and p < 0.001 respectively). Asthmatics lie in an intermediate level (0.75 Pa), but closer to thehealthy subjects, and statistically distinct from CF patients ( p < 0.01). The critical stress thus strikingly distinguishes obstructive (COPD, CF) from non-obstructive conditions (asthma, healthy), which highlights the roleof mucus dynamic (flow) properties in bronchial obstruction. Table 3 summarises the results of Bonferroni’s all
pair comparison tests performed from the ANOVA, and also includes the statistical analysis of FEV1 measurements. These results confirm the enhanced specificity of crossover measurements (Gc′ and σc ) compared to linear
moduli (G′ and G′′ at 5%) and to the FEV1 . Sputum rheology can thus much better distinguish the pathologicalconditions, especially the obstructive ones, than spirometry.
For the sake of comparison, the expected values and standard deviations for spontaneous sputa are also represented in the lower panel of Fig. 4 (open symbols; COPD and CF patients only) and summarised in Table 2.
COPD and CF levels become strikingly similar in the linear and crossover regimes.

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G5%′′ (Pa)G5%tan δ5%Gc′ (Pa)

σc (Pa)Healthy, HSS
Expected

0.14

0.047

0.35

0.012

0.27

Min–max

0.07–0.28

0.010–0.129

0.14–0.52

0.005–0.036

0.14–0.62

Asthma, HSS
Expected

0.25

0.098

0.41

0.019

0.75

Min–max

0.07–0.59

0.043–0.208

0.22–0.63

0.007–0.068

0.23–2.81

COPD, HSS
Expected

0.43

0.14

0.34

0.097

3.61

Min–max

0.09–1.88

0.03–0.44

0.21–0.48

0.024–0.327

0.87–11.91

COPD, spontaneous
Expected

1.15

0.33

0.31

0.31

11.77

Min–max

0.10–5.54

0.05–1.12

0.20–0.52

0.03–1.08

1.05–38.90

CF, HSS
Expected

0.84

0.28

0.35

0.21

6.34

Min–max

0.21–3.83

0.09–0.76

0.23–0.51

0.02–0.59

1.03–19.33

CF, spontaneous
Expected

1.24

0.41

0.34

0.32

9.68

Min–max

0.23–3.41

0.12–1.17

0.28–0.53

0.04–0.76

1.43–26.00

Table 2.  Expected and extreme values obtained from the distributions for each rheological quantity measured.

AsthmaCOPD

Cystic fibrosis

Healthy
FEV 1

1

0.360

0.009**

′
G5%

1

0.157

0.009**

′′
G5%

0.719

0.117

0.004**

Gc′

1

0.029*

0.0008***

σc

0.579

0.004**

0.0002***

Asthma
FEV 1

1

0.132

′
G5%

1

0.096

′′
G5%

1

0.156

Gc′

0.157

0.009**σc

0.095

0.005**

COPD
FEV 1

0.545

′
G5%

0.896

′′
G5%

0.636

Gc′

1

σc

1

Table 3.  Results of the ANOVA: p-values obtained from Bonferroni’s all pair comparison test. * p < 0.05;** p < 0.01; *** p < 0.001.

Discussion

To summarise, we analysed the quasi-static and dynamic rheological properties of sputum in a set of chronic
bronchial diseases. In these samples, the presence of viscoelastic inclusions of size similar to the rheometer gap
prevents meaningful rheological measurements, making homogenisation a prerequisite. Although the effects ofthis process on sputum rheology are yet to be investigated more thoroughly, our tests suggest that vortex homogenisation rather preserves the average gel properties. However, the pre-shearing of sputum samples can induce
some strain-hardening (Fig. S3), which prevents the direct comparison between homogenised and unprocessed
samples. It is thus essential to systematically process the samples according to the same protocol.
′
We identified two physical quantities characterising the quasi-static and dynamic rheological properties, G5%
and σc , which can be obtained through a standard strain sweep procedure. The stability of these characteristics
is proven robust at least over replicated measurements, and can be reasonably expected in consecutive samples

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provided that the patient remains stable. We also demonstrated that HSS induction substantially alters the sputum
rheological properties and should therefore be accounted for when comparing patients.
Taking this effect into consideration, we thus compared the rheological data obtained from healthy subjects
or with either muco-obstructive (COPD, CF) or non-obstructive (asthma) chronic bronchial diseases. We founda weak segmentation of the populations according to their sputum linear moduli, showing a gradual increase
from healthy subjects, asthmatics, then COPD and finally CF patients, the extreme conditions being typicallyone order of magnitude apart. This segmentation concerns both the storage and loss moduli alike, so that thedamping ratio remains fairly identical in all populations. Linear rheology thus proves sensitive to the specificstructure of each mucus, although structural differences between them may as well be exceeded by external elements, such as the unusual presence of biological material, that were not considered here.
Interestingly, the crossover distinguishes frankly the obstructive patients from the non-obstructive andhealthy cases, with critical stress values typically around 5–10 Pa and below 1 Pa, respectively. On the bronchial
epithelium, the force a single cilium can exert is estimated to 1 p­ N31, corresponding to a stress in the order of 1
Pa for the cilium to penetrate into the mucus layer by ≃ 1µm. To set mucus in motion at large scale, cilia mustfirst grab the mucus layer, and thus deform it plastically. The stress they exert should therefore locally exceed
the yield stress of mucus, which can be identified to σc . The comparison of this estimate with our measurementssuggests that, in chronic respiratory diseases when the mucus critical stress is increased, the effectiveness ofciliary transport falls down as cilia fail to grab the mucus layer. Especially, when the critical stress exceeds thestress cilia can exert, the mucociliary clearance would totally stop, thus favouring the bronchial obstruction byaccumulated mucus. Although this order-of-magnitude estimate should be confirmed by refined investigations
on the mucus–cilium i­ nteraction31–34, it nonetheless highlights the relevance of sputum dynamic properties, incomplement with quasi-static properties, as possible markers of chronic bronchial diseases.

Methods

Clinical protocol. We conducted a prospective, interventional, single-group assignment study. The study
protocol was approved by the local ethic committee (Comité de protection des personnes Sud Est V; Grenoble,
France IRBN6705) and registered to the national authority (ANSM) under RCB 2014-A01858-39, and research
was performed in accordance with the relevant guidelines and regulations. All subjects were informed about
the nature and purpose of the study. Each subject provided written informed consent before enrolment. Fortyfive subjects (11 healthy volunteers, 12 asthmatics, 11 COPD and 11 CF patients) were invited at the Centred’Investigation Clinique in Grenoble University Hospital on two occasions. During the first visit (t0), patientsable to expectorate spontaneously (COPD and CF) were asked to, then all participants had one or more induced
expectoration after 5, 10, 15, and/or 20 min nebulisation of a 4.5% hypertonic saline solution (HSS). The sameprocedure was repeated during the second visit (t0 + 48 h), except for CF patients who were asked to expectorate
without HSS nebulisation, 1 hour after inhaling 2.5 mL rhDNase. All patients were  18 in age and in stable state(no acute exacerbation during the preceding month), with relative FEV1 > 50% (asthmatics) or > 40% (COPD,
CF); see Supplementary Material S4, Table S2, for information on patients demographics and pulmonary function. Detailed protocol and eligibility criteria are provided in clini​caltr​ials.gov under ­NCT0268229035.
Sample preparation. Collected samples are highly heterogeneous as they consist of thick mucous inclu-

sions within a viscoelastic matrix; in addition, saliva, and bubbles inevitably collected with the sputum samples
form a watery layer on top of them. Immediately after expectoration, the saliva is removed by gently aspirating
the lower (sputum) phase with a positive displacement pipette. Sputum is transferred in a flat-bottom flask andhomogenised in vortex, typically below 6000 rpm to ensure shear rates remain under 50 s−1. This step allows to
fractionate mucous inclusions without damaging the viscoelastic properties of sputum (Supplementary Material
S5, Fig. S3)36.
After homogenisation, sputum samples are divided into aliquots (at least two, whenever possible) in orderto perform replicate measurements in a row.

Rheological measurements. Rheological measurements were performed immediately on a dedicateddevice designed and built by Rheonova, Rheomuco (Fig. S4), which consists of a strain-controlled, rotationalrheometer, working in oscillatory mode and equipped with rough plane geometries (see Supplementary Material
S6 for details).
Immediately after preparation, samples were transferred onto the rheometer’s geometry with a positive displacement pipette. Sample positioning was checked for accurate centring and excess sample was removed whenapplicable. The temperature within the gap is regulated at 37 ± 1 ◦C.
A full set of measurements consists of two consecutive frequency sweeps (0.1–5 Hz) at 5% and 10% strain,followed by a strain sweep (0.9–3000%) at 0.6 Hz. Each set of measurements typically takes 20 minutes per
replicate (including sample positioning and withdrawal), and produces the storage and loss moduli, G′ and G′′ ,as a function of frequency and strain respectively. Moduli in the linear regime were directly extracted from thefrequency sweep at 5% as they correspond to fresh samples. The crossover point was estimated by interpolationof the strain sweep curves.
Finally, the consistency of the values obtained at 5% strain from the frequency and strain sweeps was systematically controlled, measurements differing by a factor of two or above were not considered (represent ∼ 10%of total). Two samples featuring unexpectedly high linear moduli (one order of magnitude higher than othersamples from the same patient) and a linear response up to 200% strain were also ignored.
Statistical analyses. The following analyses were performed:
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www.nature.com/scientificreports/• Rheological stability—Spearman’s rank correlation tests on raw values, comparing on the one hand replicates
1 and 2 in visit 1, and on the other hand the first replicate in visits 1 and 2. This test does not require thenormality of the distribution and was thus performed with raw values. Intraclass Correlation Coefficients(ICCs) were also calculated on both raw and log-transformed values (Supplementary Material S3);
• Effect of induction—Paired Student’s t-test between spontaneous and induced sputa (bilateral after HSS,
unilateral after rhDNase as rhDNase has a documented reducing effect on sputum r­ heology13–15), on values′ and σ only);
averaged (over replicates) then log-transformed (G5%c
• Characterisation of diseases—One-way Analysis of variance (ANOVA) with Bonferroni’s all pair comparison
test after (i) per-patient all-measurements averaging, and (ii) log-transformation for log-normally-distributed
quantities (all but tan δ).

Data availability

The datasets generated and analysed during the present study are available from the corresponding author on
reasonable request.
Received: 25 March 2020; Accepted: 7 August 2020

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Acknowledgements

We wish to thank Martial Delion, Lydia Esteban, Thibaut Divoux and Jonathan T. Ma for useful discussions, andJean Thévenet, Matthieu Privat de Fortunié and the technical services of Laboratoire Rhéologie et Procédés in
Grenoble (Didier Blésès, Frédéric Hugenell) for their help in the apparatus design. We gratefully acknowledge
Dominique Abry, Nicolas Gonnet, Enkelejda Hodaj, Joane Quentin, Jean-Louis Quesada and Anne Tournier
for their help with clinical trial.

Author contributions

J.P. and E.G. planned and conceived the experiments and designed the apparatus; E.G., G.D. and M.O. performed
the rheological measurements; P.B. analysed the raw data; B.C., S.Q., J.-L.C. and C.C. supervised the medical partof the clinical trial, enrolled patients, performed the clinical experiments, collected and supplied the sputum
samples; M.R.S.V. analysed the results and wrote the paper. All authors reviewed the manuscript.

Competing interests

J.P., E.G., G.D., M.O., P.B. and M.R.D.S.V. are full-time employees of Rheonova. Rheonova designed and built
the rheometer used in this study, and funded the clinical trial. A patent pertaining to the results presented in
the present paper has been filed under the Patent Cooperation Treaty (French Institut National de la PropriétéIntellectuelle, application FR1903302). B.C., S.Q., J.-L.C. and C.C. declare no competing interests.

Additional information

Supplementary information is available for this paper at https​://doi.org/10.1038/s4159​8-020-72672​-6.
Correspondence and requests for materials should be addressed to M.R.d.
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