The Microbe, the Infection Enigma, and the Host

Abstract

Human infectious diseases are unique in that the discovery of their environmental trigger, the microbe, was sufficient to drive the development of extraordinarily effective principles and tools for their prevention or cure. This unique medical prowess has outpaced, and perhaps even hindered, the development of scientific progress of equal magnitude in the biological understanding of infectious diseases. Indeed, the hope kindled by the germ theory of disease was rapidly subdued by the infection enigma, in need of a host solution, when it was realized that most individuals infected with most infectious agents continue to do well. The root causes of disease and death in the unhappy few remained unclear. While canonical approaches in vitro (cellular microbiology), in vivo (animal models), and in natura (clinical studies) analyzed the consequences of infection with a microbe, considered to be the cause of disease, in cells, tissues, or organisms seen as a uniform host, alternative approaches searched for preexisting causes of disease, particularly human genetic and immunological determinants in populations of diverse individuals infected with a trigger microbe.

Keywords: anticytokine autoantibodies; genetic theory; host theory; inborn errors of immunity; infectious diseases; microbial theory.

Figure 1.

Estimated numbers of microbial species (A) and genera (B) that can infect and harm humans, regardless of the proportion of infected individuals that actually become sick. Numbers were obtained for virus species from (48) and estimated for genera with (99; 123), for bacteria species and genera from (12), for fungal species from (44) and estimated for genera with (75; 125), and for parasite species and genera from (89). Panel C displays a putatively linear relationship between this number of human pathogenic microbes (y-axis) and the infection fatality ratio (IFR) (x-axis). The IFR is an estimate of the proportion of deaths among infected people in the absence of treatment. Infected individuals include not only diagnosed patients (cases) with asymptomatic or symptomatic infection, but also undiagnosed individuals, based on retrospective evidence (serological or otherwise) at population level. “Untreated deaths” are the clinical outcome in the absence of medical intervention. The IFR is very difficult to estimate for most infectious diseases, due to both the often unknown proportion of undiagnosed infections and the nature of medical care, which varies greatly according to the period and region considered. The IFR is always lower, and often much lower, than the case fatality rate (CFR), which is the proportion of people diagnosed with a condition who die from it. Based in part on the list of CFRs provided by https://en.wikipedia.Norg/wiki/List_of_human_disease_case_fatality_rates, we estimate that fewer than 10 microbial species have an IFR >10%, and less than 30 have an IFR > 1% in the general population in the absence of specific treatment. In this figure, we have extrapolated the data for lower IFRs, assuming a log-linear relationship between the IFR and the number of pathogenic microbes. We used an estimated number of microbe species of 2,931 (see figure 1A), not taking into account the large number of subspecies or strains within each microbial species, as illustrated by a recent seasonal influenza virus and the 1918 pandemic influenza A virus (IAV). The figure displays some examples of microbes and their associated diseases.

Figure 1.

Estimated numbers of microbial species (A) and genera (B) that can infect and harm humans, regardless of the proportion of infected individuals that actually become sick. Numbers were obtained for virus species from (48) and estimated for genera with (99; 123), for bacteria species and genera from (12), for fungal species from (44) and estimated for genera with (75; 125), and for parasite species and genera from (89). Panel C displays a putatively linear relationship between this number of human pathogenic microbes (y-axis) and the infection fatality ratio (IFR) (x-axis). The IFR is an estimate of the proportion of deaths among infected people in the absence of treatment. Infected individuals include not only diagnosed patients (cases) with asymptomatic or symptomatic infection, but also undiagnosed individuals, based on retrospective evidence (serological or otherwise) at population level. “Untreated deaths” are the clinical outcome in the absence of medical intervention. The IFR is very difficult to estimate for most infectious diseases, due to both the often unknown proportion of undiagnosed infections and the nature of medical care, which varies greatly according to the period and region considered. The IFR is always lower, and often much lower, than the case fatality rate (CFR), which is the proportion of people diagnosed with a condition who die from it. Based in part on the list of CFRs provided by https://en.wikipedia.Norg/wiki/List_of_human_disease_case_fatality_rates, we estimate that fewer than 10 microbial species have an IFR >10%, and less than 30 have an IFR > 1% in the general population in the absence of specific treatment. In this figure, we have extrapolated the data for lower IFRs, assuming a log-linear relationship between the IFR and the number of pathogenic microbes. We used an estimated number of microbe species of 2,931 (see figure 1A), not taking into account the large number of subspecies or strains within each microbial species, as illustrated by a recent seasonal influenza virus and the 1918 pandemic influenza A virus (IAV). The figure displays some examples of microbes and their associated diseases.

Figure 2:

Studies of human infectious diseases have evolved in four major steps. All these approaches began with the identification of disease-causing microbes and were rooted in concepts proposed no later than the turn of the 20^th century, but they have matured into self-autonomous fields over different time periods. The first approach began with the detailed clinical and pathological description of diseases in the 19^th century and has more recently evolved into detailed investigations of patients with various -omics techniques (A). The second approach began at about the same time with the experimental inoculation of an animal with a microbe, initially to test one of Koch’s postulates. This approach turned out to be particularly powerful for studying infectious diseases, especially once inbred animals were generated in the 1920s, as a means of restricting and then analyzing the host component of infection outcome variability (B). The third step built on microscopic microbiological diagnostic techniques with the development of a new aim from the 1960s onward: to analyze the fate of microbes infecting cells in vitro, and the fate of the infected cells, defining the field of “cellular microbiology”, at the intersection of cell biology and molecular microbiology (C). These first three steps — A, B, C (in brown) — are part of the canonical approach, as they study the consequences of infection, which is seen as causal for disease. The fourth, alternative approach, is rooted in plant, animal, and human studies of classical genetics from the turn of the 20^th century onward, and analyses of the impact of acquired immunodeficiencies from the 1960s onward. It underwent a transition to molecular genetics with the identification of the first inborn errors of immunity (IEI) underlying an isolated infectious disease from 1996 onward. Since 2004, the discovery of autoimmune phenocopies of inborn errors of cytokines due to auto-antibodies (Auto-Abs) against various cytokines has driven further characterization of the human determinants of infectious diseases (D). This last step D (in blue) is characteristic of the alternative approach, as it sees microbial infection as an environmental trigger revealing a pre-existing cause of disease and death in the host.

Figure 3.

A selection of genetic or non-genetic risk factors associated with critical COVID-19 pneumonia or other conditions. A. Odds ratios (OR) for critical COVID-19 associated with epidemiological risk factors were obtained from (149), with TLR7 deficiency from (8), with the three most significant common variants (LZTFL1, DPP9, TYK2) from (64), with autosomal recessive (AR) or autosomal dominant (AD) inborn errors of immunity (IEI) from (90), and with autoantibodies neutralizing 10 ng/mL IFN-α and/or IFN-ω from the data from (13). B. Effects of genetic and non-genetic risk factors on other conditions. Relative risks (RR) for lung cancer were obtained from (105), for breast cancer from (139), and for tuberculosis with HIV infection from (53; 79); ORs for severe influenza were obtained from (151), for West Nile virus encephalitis from (52), for isolated congenital asplenia from (21), for pleural mesothelioma from (80), for protection against severe Plasmodium falciparum malaria from (135) with a frequency of hemoglobin AS (HbAS) from the African samples of the 1,000 genomes database, for tuberculosis in P1104A TYK2 homozygotes from (20) with a frequency of homozygotes observed in the European population, for protection from Crohn’s disease from (49) with the three most significant common variants and from (40) for P1104A TYK2 homozygotes. An OR >100 is also indicated for AR complete IFN-γ receptor (IFNGR) deficiency, for which there are more than 150 patients with complete penetrance for the syndrome of Mendelian susceptibility to mycobacterial diseases (MSMD).

Figure 3.

A selection of genetic or non-genetic risk factors associated with critical COVID-19 pneumonia or other conditions. A. Odds ratios (OR) for critical COVID-19 associated with epidemiological risk factors were obtained from (149), with TLR7 deficiency from (8), with the three most significant common variants (LZTFL1, DPP9, TYK2) from (64), with autosomal recessive (AR) or autosomal dominant (AD) inborn errors of immunity (IEI) from (90), and with autoantibodies neutralizing 10 ng/mL IFN-α and/or IFN-ω from the data from (13). B. Effects of genetic and non-genetic risk factors on other conditions. Relative risks (RR) for lung cancer were obtained from (105), for breast cancer from (139), and for tuberculosis with HIV infection from (53; 79); ORs for severe influenza were obtained from (151), for West Nile virus encephalitis from (52), for isolated congenital asplenia from (21), for pleural mesothelioma from (80), for protection against severe Plasmodium falciparum malaria from (135) with a frequency of hemoglobin AS (HbAS) from the African samples of the 1,000 genomes database, for tuberculosis in P1104A TYK2 homozygotes from (20) with a frequency of homozygotes observed in the European population, for protection from Crohn’s disease from (49) with the three most significant common variants and from (40) for P1104A TYK2 homozygotes. An OR >100 is also indicated for AR complete IFN-γ receptor (IFNGR) deficiency, for which there are more than 150 patients with complete penetrance for the syndrome of Mendelian susceptibility to mycobacterial diseases (MSMD).